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 Brain Tumor Prediction Using CNN Architecture and Augmentation Techniques: Analytical Results Subject The topic of the resource Accuracy; Automated Brain Tumor Classification; Brain Tumor Prediction; Classification; CNN; F1 Score; Machine Learning; MobileNet; Supervised Learning Algorithms; VGG-16; Xception Description An account of the resource The brain, a complex organ central to human functioning, is susceptible to the development of abnormal cell growth leading to a condition known as brain cancer. This devastating disease poses unique challenges due to the intricate nature of brain tissue, making accurate and timely diagnosis critical for effective treatment. This research explores automated brain tumor prediction through Convolutional Neural Networks (CNNs) and augmentation techniques. Utilizing a task reused learning approach with the help of VGG-16, Mobile-Net and Xception architecture, the proposed model achieves exceptional accuracy (99.54%, 99.72%) and robust metrics. This Research explores the Augmentation techniques to enhance the precision and accuracy of the model used. The study surveys related models, emphasizing advancements in automated brain tumor classification. Results demonstrate the efficacy of the model, showcasing its potential for real-world applications in medical image analysis. Future directions involve dataset expansion, alternative architectures, and incorporating explanation techniques. This research contributes to the evolving landscape of artificial intelligence in healthcare, offering a promising avenue for accurate and efficient brain tumor diagnosis. 2024 IEEE. Creator An entity primarily responsible for making the resource Mishra S.; Elappila M.; Yogish D. Source A related resource from which the described resource is derived Proceedings of InC4 2024 - 2024 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC460750.2024.10649368" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC460750.2024.10649368</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203844977&amp;doi=10.1109%2FInC460750.2024.10649368&amp;partnerID=40&amp;md5=b1551469cb4807f10cb72add283ee4b7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203844977&amp;doi=10.1109%2fInC460750.2024.10649368&amp;partnerID=40&amp;md5=b1551469cb4807f10cb72add283ee4b7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038365-2 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 Mishra S., CHRIST(Deemed to be University), Department of Computer Science and Engineering, Bangalore, India; Elappila M., CHRIST(Deemed to be University), Department of Computer Science and Engineering, Bangalore, India; Yogish D., CHRIST(Deemed to be University), Department of Computer Science and Engineering, Bangalore, India