442 20 16481 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mukhopadhyay, Debarka; Bhattacharyya, Siddhartha; Plato, Jan; Zelinka, Ivan; Snasel, Vaclav Title A name given to the resource Development ofNew Fidelity Theorems inQuantum Communication Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1508 LNNS;pp.405-417 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-8998-9_33" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-8998-9_33</a> <a href="https://www.scopus.com/pages/publications/105028250224?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028250224?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukhopadhyay D., Department of Computer Science and Engineering, Christ University, Bangalore, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic; Plato J., VSB Technical University of Ostrava, Ostrava, Czech Republic; Zelinka I., VSB Technical University of Ostrava, Ostrava, Czech Republic; Snasel V., VSB Technical University of Ostrava, Ostrava, Czech Republic Description An account of the resource Fidelity estimates the closeness or degree of overlap between a pair of unknown quantum systems. In quantum information processing study, a primary task is to estimate the fidelity of a pure states pair in a 2-dimensional Hilbert space or between a mixed state, ?, and pure state existing in N dimensional Hilbert space while transmitting them through noisy environments. This paper suggests two theorems to estimate fidelity while proving and justifying them numerically. The first theorem computes fidelity between pure states and the second estimates fidelity between mixed and pure states. The mathematical basis of the theorems confirms accuracy in estimation while dealing with single- and multiqubit system environments. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Fidelity; No cloning theorem; Quantum computing; Quantum state; Qubits Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981968997-2; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mukhopadhyay, Debarka; Bhattacharyya, Siddhartha; Platos, Jan; Zelinka, Ivan; Snasel, Vaclav; Palodhi, Kanik Title A name given to the resource Recent Advancements inPhotonic Quantum Computation Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies;Volume;274;pp.73-84 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-032-07326-6_7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-07326-6_7</a> <a href="https://www.scopus.com/pages/publications/105020388868?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105020388868?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukhopadhyay D., Department of Computer Science and Engineering, Christ University, Bangalore, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic; Platos J., VSB Technical University of Ostrava, Ostrava, Czech Republic; Zelinka I., VSB Technical University of Ostrava, Ostrava, Czech Republic; Snasel V., VSB Technical University of Ostrava, Ostrava, Czech Republic; Palodhi K., Department of of Applied Optics and Photonics, University of Calcutta, Kolkata, India Description An account of the resource Photonic quantum computation has emerged as a promising paradigm for scalable and fault-tolerant quantum computing, leveraging the unique properties of photons, such as low decoherence and ease of manipulation. Recent advancements in integrated photonics, reduction of noise and error correction, and entanglement distribution have significantly enhanced the feasibility of large-scale photonic quantum processors. This article comprehensively reviews the latest developments in single-photon qubits, photonic quantum gates, photonic chips capable of performing quantum operations and communications, and hybrid quantum architectures. We also discuss breakthroughs in optimizing fidelity in quantum gates, reducing error rates, and chip-based quantum circuits that contribute to the rapid progress in this field. Furthermore, we analyze key challenges, including loss mitigation, ensuring the sustained preservation of quantum coherence across long distances, and the effect of temperature fluctuations and coupling between adjacent photonic waveguides while exploring potential solutions. By synthesizing recent research trends, this review aims to offer insights into the future trajectory of photonic quantum computation and its role in advancing quantum technologies. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. Subject The topic of the resource Linear and Non-linear optical devices; Photonic Quantum gates; Photonic qubits; Photons; Quantum computing Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23674512; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library https://archives.christuniversity.in/files/original/e98fee455d33068e929918dedc12cc2a.jpg 96e0cb74b7edc75db27cde5309115286 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A multi-layer memory enriched staticmemory system / Subject The topic of the resource Electronics Description An account of the resource Patent Number: 202141039100, Applicant: Debarka Mukhopadhyay. The present invention is configured with the generation of multiprocessor core of each 15 bit CAM cell and a section works at a lower supply area which will drive a part to work at a more prominent induced voltage for the CAM core processor. The present device is configured in such a way so that no level converters are required. The system operates avoiding the power overhead and low supply area as illustrated in Fig1. This process is used assorting voltage with less area interface inside the CAM cells, related by the applying product on D-FF. The match line indicates the search word and stored word are indistinguishable (the match case) or are extraordinary (a confounding case, or miss) of the CAM cell. Creator An entity primarily responsible for making the resource Mukhopadhyay, Debarka. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1LliFnGKmSWAo9k5SCzLTlzQyvQRbkkHQ/view" target="_blank" title="A multi-layer memory enriched staticmemory system /" rel="noreferrer noopener">https://drive.google.com/file/d/1LliFnGKmSWAo9k5SCzLTlzQyvQRbkkHQ/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2021-05-06 Language A language of the resource English Type The nature or genre of the resource Patent https://archives.christuniversity.in/files/original/5d8af650e0dadf17adcfd1a1fda9f002.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A molecular QCA based UV lamp for water purification / Subject The topic of the resource Nano Technology Description An account of the resource Patent Number: 201731011405, Applicant: Dr.Paramartha Dutta. Creator An entity primarily responsible for making the resource Mukhopadhyay, Debarka. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1Iqnlbv2C3O_fjgaqC61GL37EpCdraZfi/view" target="_blank" title="A molecular QCA based UV lamp for water purification /" rel="noreferrer noopener">https://drive.google.com/file/d/1Iqnlbv2C3O_fjgaqC61GL37EpCdraZfi/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-22 Language A language of the resource English Type The nature or genre of the resource Patent Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mukhopadhyay, Rishav; Jha, Deepak Title A name given to the resource Building brand loyalty in the digital age: The power of social media engagement Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Elevating Brand Loyalty With Optimized Marketing Analytics and AI;pp.133-158 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-9954-5.ch007" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-9954-5.ch007</a> <a href="https://www.scopus.com/pages/publications/105004712731?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105004712731?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukhopadhyay R., Christ University, India; Jha D., Christ University, India Description An account of the resource This book chapter aims to provide information on the role of social media as a Digital Platform or Tool for emerging brands. It aims to find how emerging brands can use social media as digital platform to enhance brand awareness, engagement, reputation and consumer loyalty. This chapter also addresses the effect of Covid-19 pandemic which accelerated social media's role in marketing, as brands sought new ways to interact with consumers online. Additionally, it underscores the increasing complexity of brand loyalty in social media era where influencer marketing significantly impacts consumer perception. The Chapter also reveals the importance of Instagram marketing for emerging brands in building brand awareness. It also helps in fostering engagement with consumers, driving brand loyalty to create a strong online presence and differentiate themselves in the competitive market. 2025 by IGI Global Scientific Publishing. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836939956-9; 979-836939954-5; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Tunable Capacitive Behavior in Metallopolymer-based Electrochromic Thin Film Supercapacitors Subject The topic of the resource capacitance; coordination polymers; electrochromic; metal-organic; supercapacitors Description An account of the resource Volumetric capacitance is a more critical performance parameter for rechargeable power supply in lightweight and microelectronic devices as compared to gravimetric capacitance in larger devices. To this end, we report three electrochromic metallopolymer-based electrode materials containing Fe2+as the coordinating metal ion with high volumetric capacitance and energy densities in a symmetric two-electrode supercapacitor setup. These metallopolymers exhibited volumetric capacitance up to 866.2 F cm-3at a constant current density of 0.25 A g-1. The volumetric capacitance (poly-Fe-L2: 544.6 F cm-3> poly-Fe-L1: 313.8 F cm-3> poly-Fe-L3: 230.8 F cm-3at 1 A g-1) and energy densities (poly-Fe-L2: 75.5 mWh cm-3> poly-Fe-L1: 43.6 mWh cm-3> poly-Fe-L3: 31.2 mWh cm-3) followed the order of the electrical conductivity of the metallopolymers and are among the best values reported for metal-organic systems. The variation in the ligand structure was key toward achieving different electrical conductivities in these metallopolymers with excellent operational stability under continuous cycling. High volumetric capacitances and energy densities combined with tunable electro-optical properties and electrochromic behavior of these metallopolymers are expected to contribute to high performance and compact microenergy storage systems. We envision that the integration of smart functionalities with thin film supercapacitors would warrant the surge of miniaturized on-chip microsupercapacitors integrated in-plane with other microelectronic devices for wearable applications. 2022 American Chemical Society. All rights reserved. Creator An entity primarily responsible for making the resource Mukkatt I.; Mohanachandran A.P.; Nirmala A.; Patra D.; Sukumaran P.A.; Pillai R.S.; Rakhi R.B.; Shankar S.; Ajayaghosh A. Source A related resource from which the described resource is derived ACS Applied Materials and Interfaces, Vol-14, No. 28, pp. 31900-31910. Publisher An entity responsible for making the resource available American Chemical Society Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1021/acsami.2c05744" target="_blank" rel="noreferrer noopener">https://doi.org/10.1021/acsami.2c05744</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134854541&doi=10.1021%2Facsami.2c05744&partnerID=40&md5=a93cb23faa4c1a413ad99721b5295583" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134854541&doi=10.1021%2facsami.2c05744&partnerID=40&md5=a93cb23faa4c1a413ad99721b5295583</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19448244; PubMed ID: 35791964 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukkatt I., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Mohanachandran A.P., Material Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Department of Physics, University of Kerala, Kerala, Thiruvananthapuram, 695581, India; Nirmala A., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Patra D., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Sukumaran P.A., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Pillai R.S., Department of Chemistry, Christ University, Karnataka, Bangalore, 560029, India; Rakhi R.B., Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India, Material Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India; Shankar S., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Ajayaghosh A., Photosciences and Photonics Section, Chemical Sciences and Technology Division, CSIR - National Institute for Interdisciplinary Sciences and Technology (CSIR - NIIST), Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource CMT-CNN: colposcopic multimodal temporal hybrid deep learning model to detect cervical intraepithelial neoplasia Subject The topic of the resource Attention mechanism; Cervical cancer; Deep learning; EfficientNet; Specular reflections Description An account of the resource Cervical cancer poses a significant threat to women's health in developing countries, necessitating effective early detection methods. In this study, we introduce the Colposcopic Multimodal Temporal Convolution Neural Network (CMT-CNN), a novel model designed for classifying cervical intraepithelial neoplasia by leveraging sequential colposcope images and integrating extracted features with clinical data. Our approach incorporates Mask R-CNN for precise cervix region segmentation and deploys the EfficientNet B7 architecture to extract features from saline, iodine, and acetic acid images. The fusion of clinical data at the decision level, coupled with Atrous Spatial Pyramid Pooling-based classification, yields remarkable results: an accuracy of 92.31%, precision of 90.19%, recall of 89.63%, and an F-1 score of 90.72. This achievement not only establishes the superiority of the CMT-CNN model over baselines but also paves the way for future research endeavours aiming to harness heterogeneous data types in the development of deep learning models for cervical cancer screening. The implications of this work are profound, offering a potent tool for early cervical cancer detection that combines multimodal data and clinical insights, potentially saving countless lives. 2024, Universitas Ahmad Dahlan. All rights reserved. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived International Journal of Advances in Intelligent Informatics, Vol-10, No. 2, pp. 317-332. Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.26555/ijain.v10i2.1527" target="_blank" rel="noreferrer noopener">https://doi.org/10.26555/ijain.v10i2.1527</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201378902&doi=10.26555%2Fijain.v10i2.1527&partnerID=40&md5=a5e8814cc8b34089037f3d24f32fa92f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201378902&doi=10.26555%2fijain.v10i2.1527&partnerID=40&md5=a5e8814cc8b34089037f3d24f32fa92f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 24426571 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST(Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST(Deemed to be University), Kengeri, Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource EGMM: removal of specular reflection with cervical region segmentation using enhanced Gaussian mixture model in cervix images Subject The topic of the resource Cervical region; Colposcopy; Enhanced Gaussian mixture model; Mexican axolotl optimization; Specular reflection Description An account of the resource Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance.Before segmenting the cervical region, specular reflection removal is an efficient one. Because, cervical cancer can be found using a visual check with acetic acid, which turns precancerous and cancerous areas whiteand these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-whiteareas and should therefore be removed. So, in this paper, specular reflection removal with segmentingthe cervix region ina colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican Axolotl Optimization (AMAO) algorithm. The performance of the proposed approach is analyzed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Multimedia Tools and Applications Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11042-024-19035-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11042-024-19035-9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190708576&doi=10.1007%2Fs11042-024-19035-9&partnerID=40&md5=ecfbc67782ec0e407bb5d6de20ccc995" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190708576&doi=10.1007%2fs11042-024-19035-9&partnerID=40&md5=ecfbc67782ec0e407bb5d6de20ccc995</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 13807501; CODEN: MTAPF Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India; Thomas J., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Media's influence on suicide: Building a safer online world for all Subject The topic of the resource Media; Psychiatry; Social Media; Suicide Description An account of the resource In 1999, World Health Organization (WHO) initiated a global campaign focused on suicide prevention. In collaboration with International Association for Suicide Prevention, WHO compiled recommendations and resources intended to educate various societal and groups with the potential to impact suicide prevention, and this included the media. In order to combat the alarmingly high incidence of suicides (Tandon and Nathani, 2018), it is imperative to institute guidelines outlining how the social media forums ought to disseminate altruistic, essential educational content while. This work is a step toward achieving the same by laying down guidelines that could potentially reduce the suicide rate. 2023 Elsevier B.V. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Asian Journal of Psychiatry, Vol-91 Publisher An entity responsible for making the resource available Elsevier B.V. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.ajp.2023.103868" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ajp.2023.103868</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180563467&doi=10.1016%2Fj.ajp.2023.103868&partnerID=40&md5=a1fa1109bdf227e00fdae206f344a67a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180563467&doi=10.1016%2fj.ajp.2023.103868&partnerID=40&md5=a1fa1109bdf227e00fdae206f344a67a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18762018; PubMed ID: 38141541 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri Campus, Bangalore, 560065, India; Thomas J., CHRIST (Deemed to be University), Kengeri Campus, Bangalore, 560065, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TelsNet: temporal lesion network embedding in a transformer model to detect cervical cancer through colposcope images Subject The topic of the resource Cervical cancer; Colposcopy; Deep learning; Lesions; Transformer architecture Description An account of the resource Cervical cancer ranks as the fourth most prevalent malignancy among women globally. Timely identification and intervention in cases of cervical cancer hold the potential for achieving complete remission and cure. In this study, we built a deep learning model based on self-attention mechanism using transformer architecture to classify the cervix images to help in diagnosis of cervical cancer. We have used techniques like an enhanced multivariate gaussian mixture model optimized with mexican axolotl algorithm for segmenting the colposcope images prior to the Temporal Lesion Convolution Neural Network (TelsNet) classifying the images. TelsNet is a transformer-based neural network that uses temporal convolutional neural networks to identify cancerous regions in colposcope images. Our experiments show that TelsNet achieved an accuracy of 92.7%, with a sensitivity of 73.4% and a specificity of 82.1%. We compared the performance of our model with various state-of-the-art methods, and our results demonstrate that TelsNet outperformed the other methods. The findings have the potential to significantly simplify the process of detecting and accurately classifying cervical cancers at an early stage, leading to improved rates of remission and better overall outcomes for patients globally. 2023, Universitas Ahmad Dahlan. All rights reserved. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived International Journal of Advances in Intelligent Informatics, Vol-9, No. 3, pp. 502-523. Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.26555/ijain.v9i3.1431" target="_blank" rel="noreferrer noopener">https://doi.org/10.26555/ijain.v9i3.1431</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178487120&doi=10.26555%2Fijain.v9i3.1431&partnerID=40&md5=9830a12b831c8e3d2215c2966162d27a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178487120&doi=10.26555%2fijain.v9i3.1431&partnerID=40&md5=9830a12b831c8e3d2215c2966162d27a</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 24426571 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition Subject The topic of the resource Deep learning; Emotion recognition; Facial image analysis; LBP-TOP; Micro-expression recognition; Micro-expressions; Optical flow Description An account of the resource Facial expression analysis to understand human emotion is the base for affective computing. Until the last decade, researchers mainly used facial macro-expressions for classification and detection problems. Micro-expressions are the tiny muscle moments in the face that occur as responses to feelings and emotions. They often reveal true emotions that a person attempts to suppress, hide, mask, or conceal. These expressions reflect a persons real emotional state. They can be used to achieve a range of goals, including public protection, criminal interrogation, clinical assessment, and diagnosis. It is still relatively new to utilize computer vision to assess facial micro-expressions in video sequences. Accurate machine analysis of facial micro-expression is now conceivable due to rapid progress in computational methodologies and video acquisition methods, as opposed to a decade ago when this had been a realm of therapists and assessment seemed to be manual. Even though the research of facial micro-expressions has become a longstanding topic in psychology, this is still a comparatively recent computational science with substantial obstacles. This paper a provides a comprehensive review of current databases and various deep learning methodologies to analyze micro-expressions. The automation of these procedures is broken down into individual steps, which are documented and debated. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-163, pp. 1-16. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-0609-3_1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-0609-3_1</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162243130&doi=10.1007%2F978-981-99-0609-3_1&partnerID=40&md5=10d98068524374cf275e860c3cc094f6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162243130&doi=10.1007%2f978-981-99-0609-3_1&partnerID=40&md5=10d98068524374cf275e860c3cc094f6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, 560064, India; Thomas J., CHRIST (Deemed to be University), Bangalore, 560064, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Attention Based Meta-Module to Integrate Cervigrams with Clinical Data for Cervical Cancer Identification Subject The topic of the resource attention; cervical cancer; Deep learning; EfficientNet; feature integration Description An account of the resource Cervical cancer remains a significant burden on public health, particularly in developing countries, where its malignancy and mortality rates are alarmingly high. Early diagnosis stands as a pivotal factor in effectively treating and potentially curing the cervical cancer. This study introduces a novel approach of meta module based on recurrent gate architecture designed to enhance the classification of cervix images efficiently. This innovative framework incorporates a meta module capable of dynamically selecting image modalities most pertinent attributes. Furthermore, it integrates clinical data with extracted image features and employs a range of EfficientNet architectures (B0-B5) for image classification. Our results indicate that the EfficientNet B5 architecture outperforms its counterparts, achieving an AUC (Area Under the Curve) score of 55.1 and an F1-Score of 75.1. Overall, this work represents a crucial step towards improving the early detection of cervical cancer, which in turn can lead to more effective treatment strategies and, ultimately, better outcomes for patients worldwide. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 286-295. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_30" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_30</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200692709&doi=10.1007%2F978-3-031-64813-7_30&partnerID=40&md5=545245aa0af99f5a209eaab737f97bd0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200692709&doi=10.1007%2f978-3-031-64813-7_30&partnerID=40&md5=545245aa0af99f5a209eaab737f97bd0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration Subject The topic of the resource cervical cancer; Deep learning; DenseNet121; feature integration; K means; ResNet50 Description An account of the resource Cervical cancer ranks as the fourth most common malignancy worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this study, we introduce an ensemble of machine learning and deep learning models, including DenseNet 121, ResNet 50, and XGBoost to classify the cervical intraepithelial neoplasia. A novel feature integration is proposed which ensembles the results of the individual models in five fold validation process. Our methodology is deployed on a dataset sourced from the International Agency for Cancer Research. The results from the proposed framework have shown to be accurate, robust and dependable. This method can be utilized for achieving automatic identification of cervical cancer in early stages so it can be treated appropriately. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 112-122. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_13</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200691505&doi=10.1007%2F978-3-031-64813-7_13&partnerID=40&md5=e8f4c4443908cd4c68c99cd1930fe79a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200691505&doi=10.1007%2f978-3-031-64813-7_13&partnerID=40&md5=e8f4c4443908cd4c68c99cd1930fe79a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparative Performance Analysis of Deep Learning Models in Cervical Cancer Detection Subject The topic of the resource AlexNet; cervical cancer; Deep learning; DenseNet121; feature integration; ResNet50; VGG16 Description An account of the resource Cervical cancer one of the four most common malignancies worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this paper, we deploy a range of deep learning methods, including DenseNet 121, ResNet 50, AlexNet and VGG 16 to classify the cervical intraepithelial neoplasia. Our methodology is deployed on a dataset sourced from a Cancer Research institute in India. The current experiment aims to establish the execution of the state-of-the-art pretrained frameworks in deep learning. This will be a baseline experiment for researcher who aim to develop further deep learning models for cervical cancer diagnosis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 185-194. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_20" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_20</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200687527&doi=10.1007%2F978-3-031-64813-7_20&partnerID=40&md5=a735c134e330a3e680a3e05dd9256d81" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200687527&doi=10.1007%2f978-3-031-64813-7_20&partnerID=40&md5=a735c134e330a3e680a3e05dd9256d81</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to Be University), Bangalore, India; Thomas J., CHRIST (Deemed to Be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource CeLaTis: A Large Scale Multimodal Dataset with Deep Region Network to Diagnose Cervical Cancer Subject The topic of the resource cervical cancer; colposcope image; dataset; Deep learning; segmentation Description An account of the resource Cervical cancer is a leading cause of mortality in third world countries. Although there are multiple ways of screening cervical cancer, colposcope image analysis is considered to be standard routine method of diagnosis. Due to factors like lack of skilled personnel and interobserver variability, there is a need for automated diagnostic support for cervical cancer. However, artificial intelligence solutions for medical image analysis done through deep and machine learning models require high quality, non-erroneous and sufficient amount of data. Owing to the lack of such established benchmark datasets for the colposcope images, this work aims at establishing a standard benchmark multi state colposcope image dataset that also contains clinical findings pertaining to each case. In order to establish the quality of the images, mask R-CNN method is used for segmenting the images. Subsequently, a series of IMAGENet pretrained deep learning models are deployed on the dataset to evaluate the performance. The dataset will be made available upon request for strictly research purposes. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 154-163. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_17" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_17</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200677764&doi=10.1007%2F978-3-031-64813-7_17&partnerID=40&md5=74efcdd17038cef3cdd8aa230879dc14" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200677764&doi=10.1007%2f978-3-031-64813-7_17&partnerID=40&md5=74efcdd17038cef3cdd8aa230879dc14</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Advanced Cervical Lesion Detection using Deep Learning Techniques Subject The topic of the resource cervical cancer; cervigram; cervix; colposcope; Segmentation Description An account of the resource Cervical cancer has been one of the common causes for mortality by cancer in women across the world. But there are currently not enough skilled colposcopists, and the training process is drawn out. This implicates that there is a significant scope for artificial intelligence based computational models for segmentation of colposcope images. This paper proposes a segmentation network to accurately segment the cervix region and acetowhite lesions in a cervigram. This research can lay a foundation for research aiming to classify the cervix malignancy using AI. The method performed with a precision of 0.73870.1541, accuracy of 0.9291, recall of 0.79120.1439, a dice score of 0.74310.1506 and specificity of 0.95890.0131. The results prove that the model is reliable and robust. 2024 IEEE. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived 2024 1st International Conference on Communications and Computer Science, InCCCS 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/INCCCS60947.2024.10593544" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INCCCS60947.2024.10593544</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200566206&doi=10.1109%2FINCCCS60947.2024.10593544&partnerID=40&md5=12886896f7f7dd3a5b426199c734264f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200566206&doi=10.1109%2fINCCCS60947.2024.10593544&partnerID=40&md5=12886896f7f7dd3a5b426199c734264f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835035885-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Thomas J., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Lesion Feature Engineering Technique Based on Gaussian Mixture Model to Detect Cervical Cancer Subject The topic of the resource Cervical cancer; Deep learning; Expectation maximization; Gaussian mixture modelling; Lesion feature extraction; Segmentation Description An account of the resource Latest innovations in technology and computer science have opened up ample scope for tremendous advances in the healthcare field. Automated diagnosis of various medical problems has benefitted from advances in machine learning and deep learning models. Cancer diagnosis, prognosis prediction and classification have been the focus of an immense amount of research and development in intelligent systems. One of the major concerns of health and the reason for mortality in women is cervical cancer. It is the fourth most common cancer in women, as well as one of the top reasons of mortality in developing countries. Cervical cancer can be treated completely if it is diagnosed in its early stages. The acetowhite lesions are the critical informative features of the cervix. The current study proposes a novel feature engineering strategy called lesion feature extraction (LFE) followed by a lesion recognition algorithm (LRA) developed using a deep learning strategy embedded with a Gaussian mixture model with expectation maximum (EM) algorithm. The model performed with an accuracy of 0.943, sensitivity of 0.921 and specificity of 0.891. The proposed method will enable early, accurate diagnosis of cervical cancer. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-868, pp. 63-75. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-9037-5_6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9037-5_6</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189544119&doi=10.1007%2F978-981-99-9037-5_6&partnerID=40&md5=d88ec727023159202c272d46379d2b4f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189544119&doi=10.1007%2f978-981-99-9037-5_6&partnerID=40&md5=d88ec727023159202c272d46379d2b4f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999036-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University) Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University) Kengeri, Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Multimodal Early Fusion Strategy Based on Deep Learning Methods for Cervical Cancer Identification Subject The topic of the resource Cervical cancer; Deep learning; Early fusion Description An account of the resource It is essential to enhance the accuracy of automatic cervical cancer diagnosis by combining multiple forms of information obtained from a patients primary examination. However, existing multimodal systems are not very effective in detecting correlations between different types of data, leading to low sensitivity but high specificity. This study introduces a deep learning system for automatic diagnosis of cervical cancer by incorporating multiple sources of data. First, a convolutional neural network (CNN) to transform the image database to a vector that can be combined with non-image datasets is used. Subsequently, an investigation of jointly the nonlinear connections between all image and non-image data in a deep neural network is performed. Proposed deep learning-based method creates a unified system that takes advantage of both image and non-image data. It achieves an impressive 89.32% sensitivity at 91.6% specificity when diagnosing cervical intraepithelial neoplasia on a wide-ranging dataset. This result is far superior to any single-source system or prior multimodal approaches. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-865, pp. 109-118. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-9043-6_9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9043-6_9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190394982&doi=10.1007%2F978-981-99-9043-6_9&partnerID=40&md5=0a7b74b039f5d9d7ea7ef150d3a00f3e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190394982&doi=10.1007%2f978-981-99-9043-6_9&partnerID=40&md5=0a7b74b039f5d9d7ea7ef150d3a00f3e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999042-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Specular Reflection Removal Techniques in Cervix Image: A Comprehensive Review Subject The topic of the resource Biomedical image analysis; Cervical cancer; Gaussian mixture model; Morphological top-hat transform; Specular reflection Description An account of the resource Cancer detection through medical image segmentation and classification is possible owing to the advancement in image processing techniques. Segmentation and classification tasks carried out to predict and classify diseases need to be dependable and precise. Specular reflections are the high-intensity and low-saturation areas that reflect the light from the probing devices that capture the picture of the organ surface. These areas sometimes mimic the features that are key identifying factors for cancers like acetowhite lesions. This review article examines the various methods proposed for removing specular reflections from medical images, especially those captured by colposcope. The fundamentals of specular reflection removal and its associated challenges are discussed. The paper reviews several state-of-the-art approaches for specular reflection removal. The comprehensive review can be a strong foundation for researchers looking to decide on appropriate techniques to employ in their respective research approaches. 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering, Vol-1105, pp. 479-490. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-7633-1_36" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-7633-1_36</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182518157&doi=10.1007%2F978-981-99-7633-1_36&partnerID=40&md5=77d3a10b252efd858f5e0ae6c8bf6c7f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182518157&doi=10.1007%2f978-981-99-7633-1_36&partnerID=40&md5=77d3a10b252efd858f5e0ae6c8bf6c7f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18761100; ISBN: 978-981997632-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Specular Reflection Removal Technique in Cervigrams Subject The topic of the resource cervix; HSI images; preprocessing; specular inpainting; specular reflections Description An account of the resource Cancer detection through medical image segmentation and classification is possible owing to the advancement in image processing techniques. Segmentation and classification tasks carried out to predict and classify diseases need to be dependable and precise. Specular reflections are the high-intensity and low-saturation areas that reflect the light from the probing devices that capture the picture of the organ surface. These areas sometimes mimic the features that are key identifying factors for cancers like acetowhite lesions. This review article examines the various methods proposed for removing specular reflections from medical images, especially those captured by colposcopes. The fundamentals of specular reflection removal and its associated challenges are discussed. The paper reviews several prominent approaches for removal of specular reflections proposes a novel method to remove the specular reflections. The comprehensive review can be a strong foundation for researchers looking to decide on appropriate techniques to employ in their respective research approaches. 2023 IEEE. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC457730.2023.10263224" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC457730.2023.10263224</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174726543&doi=10.1109%2FInC457730.2023.10263224&partnerID=40&md5=ba42fd9920e04a3c694a02dc4b77ccbf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174726543&doi=10.1109%2fInC457730.2023.10263224&partnerID=40&md5=ba42fd9920e04a3c694a02dc4b77ccbf</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033577-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Thomas J., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India