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 Machine Learning Entrenched Brain Tumor Recognition Framework Subject The topic of the resource Brain tumor; Confusion matrix; Convolutional Neural Networks; Image processing; Machine learning; Mobile application Description An account of the resource Brain tumor detection plays a significant role in medical image processing. Treatment for patients with brain tumors is primarily dependent on faster detection of these tumors. More rapid detection of brain tumors will help in the improvement of the patient's life chances. Diagnosis of brain tumors by doctors most commonly follow manual segmentation, which is difficult and time-consuming; instead, automatic detection is necessary. Nowadays, automatic detection plays a vital role and can be a solution to detecting brain tumors with better performance. Brain tumor detection using the MRI images method is an essential diagnostic tool for predicting brain tumors; the implementation for these kinds of detection can be done using various machine learning algorithms and methodologies. It helps the doctors understand the actual progression of the evolving tumor, allowing the doctors to decide how the treatment has to be given for that particular patient and measures required to follow up. Therefore, the intention is to create a framework to detect brain tumors in MRI images using a machine learning algorithm and analyze the performance of the brain tumor detection using sensitivity and specificity, which helps us to analyze how well the algorithm has performed in detecting the brain tumors accurately and develop a mobile application framework in which the MRI images can be directly scanned to know whether the cancer is present in a scanned MRI image or not. 2022 IEEE. Creator An entity primarily responsible for making the resource Surya S.; Aurelia S. Source A related resource from which the described resource is derived Proceedings of the International Conference on Electronics and Renewable Systems, ICEARS 2022, pp. 1372-1376. 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 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICEARS53579.2022.9752195" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEARS53579.2022.9752195</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128934305&amp;doi=10.1109%2FICEARS53579.2022.9752195&amp;partnerID=40&amp;md5=ff25dcfe71bdddc3401add20e04b2c34" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128934305&amp;doi=10.1109%2fICEARS53579.2022.9752195&amp;partnerID=40&amp;md5=ff25dcfe71bdddc3401add20e04b2c34</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548425-1 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 Surya S., Christ University, Dept. Computer Science, Bangalore, India; Aurelia S., Christ University, Dept. Computer Science, Bangalore, India