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                <text>Improved Deep Learning Model for Detection and Classification of Pneumonia from X-Ray Images  </text>
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                <text>Pneumonia is a severe respiratory disease that can lead to inflammation, fluid accumulation in lungs and breathing difficulties, which needs immediate and accurate diagnosis. Chest X-Ray images are a necessary tool to diagnose pneumonia because manual interpretation poses challenges, particularly for radiologists with less expertise. Artificial intelligence (AI), specifically Convolutional Neural Networks (CNNs), has become a significant in the field of pneumonia detection within chest X-Ray images in recent years. This research presents SarNet, a neural network model developed for the identification of pneumonia in chest X-Ray images. The study involved the compilation of dataset containing chest X-Ray images categorized as normal, pneumonia, and COVID-19 pneumonia cases, each accompanied by appropriate annotations. This dataset was employed as the basis for training and assessing SarNet's performance, underscoring its promise in transforming the diagnosis of pneumonia. SarNet proved highly effective, achieving good accuracy, sensitivity, and specificity compared to traditional diagnostic methods. The model's simplicity, with 41 layers, strikes a balance between depth and computational complexity, enhancing efficiency and ensuring accurate pneumonia detection. Furthermore, the study expanded its scope to include COVID-19 pneumonia detection. SarNet achieved an accuracy of 99.15% in binary classification and 94.9% in multiclass classification, including healthy, pneumonia, and COVID-19 pneumonia cases.</text>
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                <text>Vijayalakshmi, A</text>
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                <text>Fuzzy Image Processing; Internet of Things; Kinetic somatosensor</text>
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                <text>Smart wearable technologies utilising devices connected to the web (IoT) are on the rise, and many of these new applications involve the identification of athletic performance. Many people across the world participate in soccer, also called football in some regions. Soccer players practise discrete actions (like shooting and passing) in order to ingrain them in muscle memory and speed up their reflexes during actual games. There is always a compromise between blur and noise when processing images. Denoising naturally softens an image because noise is high-frequency information. Deblurring, on the other hand, causes additional noise in the final product. The need to brighten an image in low-light conditions only adds to the difficulty. Noise is introduced into the image during the brightening process itself. Images taken while moving, especially those of wildlife (though not exclusively), will have more blur than those taken while still. Many previous projects have focused on a single problem, but very few have attempted to address the entire set of problems simultaneously. So, we set out to make a way to turn these lowlight, fuzzy images into high-contrast, clear images. A fuzzy invariant space is the result of the union of several fuzzy invariant spaces. After numerous iterations of processing a blurred image, the final stage is to utilise a progressive restoration procedure. The experimental findings demonstrate the effectiveness of the suggested technique in reducing calculation error, improving the recovery effect, and avoiding the noise caused by numerous deconvolutions. This work introduces new concepts and methods for recognition research by applying fuzzy image processing to the study being human mobility and the detection of activities in the realm of IoT. Using the Kinect, an IoT somatosensory camera, we are able to collect 15 3D skeletal elements via its software development kit (SDK). This led to the study of kinesiology and the creation of a motion resolution model that works well with the Internet of Things.   2022 IEEE.</text>
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                <text>Saseekala M.; Arun Raghesh J.T.; Madhavidevi B.; Sasidevi J.; Ramalingam V.; Das S.</text>
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                <text>Proceedings of 5th International Conference on Contemporary Computing and Informatics, IC3I 2022, pp. 2075-2080.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Saseekala M., Christ University, Faculty of Computer Applications, School of Business and Management, Karnataka, Bangalore, India; Arun Raghesh J.T., Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Tamilnadu, Chennai, India; Madhavidevi B., Institute of Aeronautical Engineering, Telangana, Hyderabad, India; Sasidevi J., K Ramakrishnan College of Engineering, Department of CSE, Trichy, Samayapuram, India; Ramalingam V., University of Technology and Applied Sciences, Shinas, Oman; Das S., Jain University, Karnataka, Bengaluru, India</text>
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                <text>COBOTS: Vital role in significant domains</text>
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                <text>The term COBOT refers to "collaborative robot, " which is created by combining humans and robots to increase the efficacy and efficiency of industrial processes. Cobots have extensive applications in various sectors, including healthcare, motoring, production, electronics, space exploration, logistics, and astronomy. Industry 5.0 is a development that aims to combine human specialists' creativity with accurate, intelligent, and efficient technologies to revolutionize manufacturing processes worldwide. Therefore, in the age of Industry 5.0, there is a great demand for Cobots with high, quick advancement, and low costs. Industry evolution, fundamentals of Cobots, how they differ from robots, key features, basic components, the significant role of Cobots in Industry 5.0, challenges and limitations, future scope, and ethical aspects of Cobots are covered in this chapter. This book chapter is a comprehensive manual for academic researchers and corporate executives to learn about Cobots completely.  2024, IGI Global. All rights reserved.</text>
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                <text>Saseekala M.; Raj M.S.; Anu P.</text>
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                <text>Harnessing Artificial Emotional Intelligence for Improved Human-Computer Interactions, pp. 243-262.</text>
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                <text>Saseekala M., Christ University, Bangalore, India; Raj M.S., Vellore Institute of Technology, Vellore, India; Anu P., SASTRA University, India</text>
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                <text>Future Innovation in Healthcare by Spatial Computing using ProjectDR</text>
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                <text>3D Tracking; Augmented Reality; Medical display; ProjectDR; Rehabilitation of patients; Spatial Computing; Virtual Reality</text>
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                <text>Spatial Computation is the next step in the continuing convergence between the digital and physical realms. It is a set of inventions and developments that can better our lives through learning the real world, acknowledging and connecting our connection to, and traveling through various locations in the world. The lack of modern, precise, and effective diagnosis limits the rehabilitation of patients, despite technical advancements in medicines. The capabilities of spatial computing are expanded in a healthcare framework during the care and treatment of the patient. In this article, our purpose is to clarify the function of ProjectDR in the field of healthcare, which enables the display of medical images, such as CT scans and MRI results, directly on the patient's body in a manner that moves as patients do.   2021 IEEE.</text>
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                <text>Sasi A.; Ravichandran S.K.</text>
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                <text>Proceedings of the 3rd International Conference on Inventive Research in Computing Applications, ICIRCA 2021, pp. 829-833.</text>
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                <text>Classroom experiences contribute to learners' perceptions and interest in a particular subject. The present study aims to understand students' perception of mathematics learning by exploring their classroom experiences. The study sample consisted of 17 eighth-grade students in English-speaking urban schools in South India. The data was collected through a semi-structured interview schedule. The thematic analysis presents five themes  student personal factors, teacher-related, content-related, classroom environment and utility value. Teachers characteristics and mathematics content were the essential factors contributing to students' perceptions and experiences. The study highlights the utility value of the content to help students see the application of the subject in real-world situations. Understanding students' perception of mathematics learning would help to choose appropriate content and teaching methods in the curriculum. The study highlights the need for educational and psychological interventions, focusing on student-teacher engagement and curriculum development to enhance mathematics learning.  (2023). All Rights Reserved.</text>
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                <text>International Journal of Innovation in Science and Mathematics Education, Vol-31, No. 2, pp. 47-59.</text>
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                <text>Mathematics Self-Efficacy, Utility Value and Well-Being Among School Students in India: Mediating Role of Student Engagement</text>
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                <text>Teaching and learning mathematics has many challenges, including student engagement, attitudes and beliefs toward mathematics. Students experience stress and anxiety while learning mathematics. Mathematics is perceived as a complex subject. Student self-efficacy and a sense of utility value of mathematics topics can impact student learning and well-being. The current study aims to examine the mediating role of student engagement on the relationship between mathematics self-efficacy, utility value and well-being among students. A cross-sectional survey of 774 eighth-grade students (491 male and 283 female) from India was carried out using standardized scales to measure the study variables. The mediation analysis tested two conceptual models. The findings indicate that student engagement mediates the relationship between self-efficacy and student well-being (model 1), and student engagement mediates the relationship between utility value and student well-being (model 2). The structural equation model results indicate an acceptable fit of the tested conceptual models. The study findings call for focusing on socio-emotional aspects of mathematics learning to improve the well-being of students.  2023 Research Council on Mathematics Learning.</text>
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                <text>Investigations in Mathematics Learning, Vol-15, No. 4, pp. 266-278.</text>
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                <text>Novel Applications of Carbon Based Nano-materials, pp. 412-429.</text>
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                <text>Flavonol based surface modification of doped chalcogenide nanoflakes as an ultrasensitive fluorescence probe for Al3+ ion</text>
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                <text>A highly selective novel fluorescent probe was prepared by using surface modified ZnS:Mn nanoparticles, functionalized with morin, a flavonol. SEM investigations of the heterostructures prepared using wet chemical precipitation technique revealed a nanoflake type of morphology. HR-TEM and powder XRD analysis confirmed the crystalline planes corresponding to Wurtzite ZnS. The functionalized nanoparticles were characterized using Raman, XPS and FTIR which confirms the binding of morin to the nanoparticles via surface coordination. The prepared probe selectively interacts with Al3+ ions which has been used as an ultrasensitive analytical tool for determination of Al3+ ions. A major advantage of the proposed method is that the other metal ions closely associated with Al3+ did not interfere with the analysis. The detection limit and the quantitation limit were found to be 0.07 nM and 0.20 nM respectively with a linear dynamic range 0.20 nM80 nM. The method was successfully applied to environmental water samples and other complex matrices.  2017 Elsevier B.V.</text>
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                <text>Sasitharan K., Department of chemistry, Christ University, Bangalore, 560 029, India; Varghese A., Department of chemistry, Christ University, Bangalore, 560 029, India; George L., Department of chemistry, Christ University, Bangalore, 560 029, India</text>
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                <text>Novel Applications of Carbon Based Nano-materials, 1st ed., pp.412-429, eBook ISBN : 9781003183549.</text>
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                <text>&lt;a href="https://www.taylorfrancis.com/chapters/edit/10.1201/9781003183549-26/biomass-derived-carbonaceous-materials-synthesis-photocatalytic-applications-kezia-sasitharan-anitha-varghese" target="_blank" title="Biomass-derived carbonaceous materials: Synthesis and photocatalytic applications" rel="noreferrer noopener"&gt;https://www.taylorfrancis.com/chapters/edit/10.1201/9781003183549-26/biomass-derived-carbonaceous-materials-synthesis-photocatalytic-applications-kezia-sasitharan-anitha-varghese&lt;/a&gt;</text>
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                <text>Potent of sales-persons, impact on the channel of distribution in lighting industry in bangalore</text>
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              <elementText elementTextId="132292">
                <text>Channel of Distribution; Functions of Sales Persons; Intermediaries</text>
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                <text>Its found in array of literature on the roles, functioning of the sales persons and also illuminates how these are measured on effectiveness of channel of distribution. This study made with objective for better understanding of various variables, and out of which primary factors that could be focused for effectiveness of channel of distribution in lighting industry in Bangalore from the perceptive of intermediaries. This study draws the responses from intermediaries who are pivotal force (opinion leaders) in the market, which could prove more deep understanding for strategizing the channels in the said industry. From the review of literature we streamlined the functions performed for potent of sales persons. Further analysed with vivid using various statistical tools to understand loads (Eigen value), hence, prompting with Principal Component Analysis. This study is uses all normative way to analyse of the results reframed pivotal factors, in classifying, draining out insignificant factors. By regrouping based on the array of load, we come to understand 3 vital ingredients viz., 1) intermediaries appointment criteria 2) sales training&amp;amp; communication 3) concern for cost and needs of intermediaries, and urging to business institutions to opt for better channel strategy. Notwithstanding, the relationship with intermediaries are charismatic in nature, and dynamics of channel strategy would and will be determinant for success of any business organisation.  2019, Institute of Advanced Scientific Research, Inc.. All rights reserved.</text>
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                <text>Sateesh Kumar T.K.; Basava Aradhya S.G.</text>
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                <text>Journal of Advanced Research in Dynamical and Control Systems, Vol-11, No. 5, pp. 166-172.</text>
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                <text>Institute of Advanced Scientific Research, Inc.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070802587&amp;amp;partnerID=40&amp;amp;md5=7e4523bbcc083746afe336a53c502856" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070802587&amp;amp;partnerID=40&amp;amp;md5=7e4523bbcc083746afe336a53c502856&lt;/a&gt;</text>
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                <text>Sateesh Kumar T.K., Bharthiar University, India; Basava Aradhya S.G., Global Institute of Management Science, Bangalore, India, Christ Institute of Management, Christ University, Lavasa Campus, Pune, India</text>
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                <text>AI and Machine Learning Enabled Software Defined Networks</text>
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                <text>The telecommunications industry has not been exempt from the technology sectors massive artificial intelligence (AI) and machine learning (ML) boom in recent years. Artificial intelligence (AI) and machine learning (ML) provide advanced analytics and automation that are in line with modern networking concepts like software-defined networking (SDN) and software-defined wide-area networks (SD-WAN). Work is being done to determine how AI/ML can benefit SD-WAN and to demonstrate these benefits in a real SD-WAN network using a workable example. Modern ML techniques and algorithms are the extent of AI/ML. Todays Internet is under constant threat from DDoS (Distributed Denial of Service) attacks. As the volume of Internet traffic grows, its getting harder and harder to tell whats legitimate and whats malicious. The DDoS attack was detected using a machine learning approach that makes use of a Random Forest classifier. To better detect DDoS attacks, we tweak the Random Forest algorithm. The proposed machine learning approach outperforms, as demonstrated by our results.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Satheesh K.K.S.V.A.; Janani M.; Venkateswarlu S.C.; Kumar R.G.; Gupta A.; Kotaiah B.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-446, pp. 131-144.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>Satheesh K.K.S.V.A., School of Computer Science and Artificial Intelligence, SR University, Hanuma Konda, Warangal, India; Janani M., IT Department, St. Josephs College of Engineering, Hyderabad, India; Venkateswarlu S.C., Electronics and Communication Engineering, Institute of Aeronautical Engineering, Telangana, Dundigal, Hyderabad, India; Kumar R.G., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Kengeri Campus, Bangalore, India; Gupta A., Amity Business School, Amity University, Uttar Pradesh, Greater Noida, India; Kotaiah B., Department of CS and IT, Maulana Azad National Urdu Central University, Telangana, Gachibowli, Hyderabad, India</text>
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                <text>Enhancement in air-cooling of lithium-ion battery packs using tapered airflow duct</text>
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                <text>Battery Thermal Management; Computational Fluid Dynamics; Lithium-ion Battery; Temperature Uniformity</text>
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                <text>Temperature uniformity and peak-temperature reduction of lithium-ion battery packs are critical for adequate battery performance, cycle life, and safety. In air-cooled battery packs that use conventional rectangular ducts for airflow, the insufficient cooling of cells near the duct outlet leads to temperature nonuniformity and a rise in peak temperature. This study proposes a simple method of using a converging, tapered airflow duct to attain temperature uniformity and reduce peak temperature in air-cooled lithium-ion battery packs. The conjugate forced convection heat transfer from the battery pack was investigated using computational fluid dynamics, and the computational model was validated using experimental results for a limiting case. The proposed converging taper provided to the airflow duct reduced the peak temperature rise and improved the temperature uniformity of the batteries. For the conventional duct, the boundary layer development and the increase in air temperature downstream resulted in hotspots on cells near the outlet. In contrast, for the proposed tapered duct, the flow velocity increased downstream, resulting in improved heat dissipation from the cells near the outlet. Furthermore, the study investigated the effects of taper angle, inlet velocity, and heat generation rate on the flow and thermal fields. Notably, with the increase in taper angle, owing to the increase in turbulent heat transfer near the exit, the location of peak temperature shifted from the exit region to the central region of the battery pack. The taper-induced improvement in cooling was evident over the entire range of inlet velocities and heat generation rates investigated in the study. The peak temperature rise and maximum temperature difference of the battery pack were reduced by up to 20% and 19%, respectively. The proposed method, being effective and simple, could find its application in the cooling arrangements for battery packs in electric vehicles.  2023 Y?ld?z Technical University. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). All Rights Reserved.</text>
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                <text>Satheesh V.K.; Krishna N.; Kushwah P.S.; Garg I.; Rai S.; Hebbar G.S.; Nair D.V.</text>
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                <text>Journal of Thermal Engineering, Vol-10, No. 2, pp. 375-385.</text>
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                <text>Yildiz Technical University</text>
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                <text>&lt;a href="https://doi.org/10.18186/THERMAL.1448648" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.18186/THERMAL.1448648&lt;/a&gt;
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                <text>ISSN: 21487847</text>
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                <text>Satheesh V.K., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Krishna N., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Kushwah P.S., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Garg I., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Rai S., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Hebbar G.S., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Nair D.V., Department of Mechanical Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India</text>
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                <text>Gold vs Gold Exchange Traded Funds: An Empirical Study in India</text>
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              <elementText elementTextId="128735">
                <text>Correlation; Famas Measure; Gold vs Gold ETFs; Jensens Index; Sharpes Index; Treynors Index</text>
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                <text>This study aim of this is to estimate the relationship between gold and Gold Exchange Traded Fund (ETF) and the performance of Gold ETFs in India by using various statistical models. The data for the study covers a period of three years from 2015 to 2018. The data was collected from the National Stock Exchange database and other sources. The outcome of this study was to find out whether there is a relationship between gold and Gold ETFs. It was found out that Gold ETFs has more returns than the physical gold; Axis ETF performed the best among those Gold ETFs selected for the study. This study will be beneficial for the market researchers and investors who find the best opportunities in the Gold ETFs.  2019 EA. All rights reserved.</text>
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                <text>Sathish Kumar B.; Ram Raj G.</text>
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                <text>Economic Affairs (New Delhi), Vol-64, No. 4, pp. 703-710.</text>
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              <elementText elementTextId="128742">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 4242513</text>
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                <text>Sathish Kumar B., Department of Commerce, Christ (Deemed to be University), Bengaluru, India; Ram Raj G., Department of Commerce CA, VHNSN College, Tamil Nadu, Virudhunagar, India</text>
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                <text>A complete person re-identification model using Kernel-PCA-based Gabor-filtered hybrid descriptors</text>
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              <elementText elementTextId="132681">
                <text>Deep learning; Distance metric learning; Kernel PCA; Pedestrian detection; Person re-identification; Spatial descriptor; Video surveillance</text>
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                <text>Person re-identification is a challenging problem in computer vision. Lots of research interest is observed in this area over the past few years. A model for complete person re-identification can prove useful in this direction. Use of convolutional neural networks for pedestrian detection can improve the accuracy of detection to a larger extent. Deriving a descriptor which is invariant to the changes in the illumination, background and the pose can make the difference in the re-identification process. The predominant part of our work focuses on building a robust descriptor which can tackle such challenges. We have concentrated on building a descriptor by employing appearance-based features extracted both at local and global levels. Further, the dimensionality of the descriptor is reduced using kernel PCA. Distance metric learning algorithms are used to evaluate the descriptor on three major benchmark datasets. We propose a complete person re-identification system which involves both pedestrian detection and person re-identification. Major contributions of this work are to detect pedestrians from surveillance videos using CNN-based learning and to generate a kernel-PCA-based spatial descriptor and evaluate the descriptor using known distance metric learning methods on benchmark datasets.  2018, Springer-Verlag London Ltd., part of Springer Nature.</text>
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                <text>Sathish P.K.; Balaji S.</text>
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                <text>International Journal of Multimedia Information Retrieval, Vol-7, No. 4, pp. 221-229.</text>
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                <text>ISSN: 21926611</text>
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                <text>Sathish P.K., Department of Computer Science and Engineering, Christ University, Bengaluru, 560074, India; Balaji S., Centre for Incubation, Innovation, Research and Consultancy, Jyothi Institute of Technology, Bengaluru, India</text>
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                <text>Multi-frame twin-channel descriptor for person re-identification in real-time surveillance videos</text>
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                <text>Cumulative matching curve; Multi-frame descriptor; Person re-identification; Video surveillance</text>
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                <text>Automatic re-identification of people entering the camera network is an important and challenging task. Multiple frames of the same person will be easily available in surveillance videos for re-identification. Dealing with pose variations of the person in the image and partial occlusion issues is major challenge in single-frame re-identification process. The use of more frames from the surveillance videos can generate robust descriptor to tackle issues of pose variations and occlusion. In this paper, we have emphasized on using multiple frames from the same video to generate a multi-frame twin-channel descriptor. The work deals with building a spatial-temporal descriptor which takes advantage of the twin paths to extract features of the person image. Mahalanobis distance metric learning algorithms is used for matching and evaluation. Our descriptor is evaluated on two benchmark datasets and found to surpass the performance of the existing methods.  2017, Springer-Verlag London Ltd.</text>
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                <text>Sathish P.K.; Balaji S.</text>
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                <text>International Journal of Multimedia Information Retrieval, Vol-6, No. 4, pp. 289-294.</text>
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                <text>ISSN: 21926611</text>
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                <text>Sathish P.K., Department of Computer Science and Engineering, Christ University, Bengaluru, 560074, India; Balaji S., Centre for Incubation, Innovation, Research and Consultancy, Jyothi Institute of Technology, Bengaluru, India</text>
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                <text>Person re-identification using part based hybrid descriptor</text>
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                <text>Descriptor; Person re-identification; Video surveillance system; Weighted color histogram</text>
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                <text>Real time person re-identification systems require robust descriptors for useful feature extraction. This paper focuses on a novel descriptor which can efficiently re-identify persons in varied views and change in illumination. The descriptors detect the features by dividing the person image into multiple parts. We use a combination of local and global feature descriptors to form a reliable descriptor. Performance evaluation is done on a benchmarking dataset.  2016 IEEE.</text>
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                <text>Proceedings - 2016 2nd International Conference on Cognitive Computing and Information Processing, CCIP 2016</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/CCIP.2016.7802849" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/CCIP.2016.7802849&lt;/a&gt;
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                <text>ISBN: 978-150901025-7</text>
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                <text>Sathish P.K., Computer Science and Engineering Department, Christ University, Bangalore, 560074, India; Balaji S., Centre for Emerging Technologies, Jain University, Karnataka, 562112, India</text>
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