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 Brain image classification using time frequency extraction with histogram intensity similarity Subject The topic of the resource Convolutional neural network; Differential deep learning; Histogram Description An account of the resource Brain medical image classification is an essential procedure in Computer-Aided Diagnosis (CAD) systems. Conventional methods depend specifically on the local or global features. Several fusion methods have also been developed, most of which are problem-distinct and have shown to be highly favorable in medical images. However, intensity-specific images are not extracted. The recent deep learning methods ensure an efficient means to design an end-to-end model that produces final classification accuracy with brain medical images, compromising normalization. To solve these classification problems, in this paper, Histogram and Time-frequency Differential Deep (HTF-DD) method for medical image classification using Brain Magnetic Resonance Image (MRI) is presented. The construction of the proposed method involves the following steps. First, a deep Convolutional Neural Network (CNN) is trained as a pooled feature mapping in a supervised manner and the result that it obtains are standardized intensified pre-processed features for extraction. Second, a set of time-frequency features are extracted based on time signal and frequency signal of medical images to obtain time-frequency maps. Finally, an efficient model that is based on Differential Deep Learning is designed for obtaining different classes. The proposed model is evaluated using National Biomedical Imaging Archive (NBIA) images and validation of computational time, computational overhead and classification accuracy for varied Brain MRI has been done. 2022 CRL Publishing. All rights reserved. Creator An entity primarily responsible for making the resource Renukadevi T.; Saraswathi K.; Prabu P.; Venkatachalam K. Source A related resource from which the described resource is derived Computer Systems Science and Engineering, Vol-41, No. 2, pp. 645-660. Publisher An entity responsible for making the resource available Tech Science Press 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/10.32604/csse.2022.020810" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/csse.2022.020810</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118999186&amp;doi=10.32604%2Fcsse.2022.020810&amp;partnerID=40&amp;md5=98b1dc0fc734c5734571d16676946440" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118999186&amp;doi=10.32604%2fcsse.2022.020810&amp;partnerID=40&amp;md5=98b1dc0fc734c5734571d16676946440</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 2676192; CODEN: CSSEE 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 Renukadevi T., Department of Computer Technology-UG, Kongu Engineering College, Erode, India; Saraswathi K., Department of Computer Technology-UG, Kongu Engineering College, Erode, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India