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 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/. Creator An entity primarily responsible for making the resource Kaushik, Ruchi; Pradeep, S.; Shanbhog, Manjula; Tamizhselvi, A.; Jagdale, Jayashree; Mahajan, Rashima Title A name given to the resource A novel deep learning based multimedia video retrieval framework using may fly optimization 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 International Journal of Information Technology (Singapore); Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s41870-025-02587-w" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s41870-025-02587-w</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007443959?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007443959?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 Kaushik R., Xavier Institute of Management and Entrepreneurship, Bengaluru, India; Pradeep S., Department of CSE, Malla Reddy Engineering College for Women, Maisammaguda, Kompally, Telangana, Secunderabad, India; Shanbhog M., School of Science, Christ University, Bengaluru, India; Tamizhselvi A., IT, St. Josephs College of Engineering, Chennai, India; Jagdale J., Information Technology, Pune Institute of Computer Technology, Pune, India; Mahajan R., Manav Rachna International Institute of Research and Studies, Faridabad, India Description An account of the resource Developing a video retrieval framework in multimedia management is a main challenge due to the massive growth of video content on the internet. A major drawback of video retrieval is its long search response time and low accuracy. To tackle these issues, this paper introduces a novel deep learning-based Multimedia video retrieval system (DL-MVR) to minimize the search response time with high accuracy. The collected video is initially converted into key frames and pre-processed with contrast adaptive histogram equalization to remove noise artifacts thereby improving image quality. After pre-processing, the images are fed to Efficient Net to extract patch features. Finally, to retrieve the similar video, matching is done using may fly optimization (MFO), that compares the query frame features to the video database. Several performance metrics are analysed to measure the effectiveness of the proposed strategy in terms of accuracy and response time. Experimental results indicate that the proposed system has a search response time of 0.71s, which is lower than existing methods. The proposed DL-MVR method achieves 99.26% of accuracy. The proposed method improves the overall accuracy by 9.32%, 22.04%, and 19.40% which is better than CNN-AlexNet (convolutional neural network), Pyramid regional graph network and CBVR respectively. Bharati Vidyapeeth's Institute of Computer Applications and Management 2025. Subject The topic of the resource Efficient net; Histogram equalization; May fly optimization (MFO); Multimedia; Video retrieval Publisher An entity responsible for making the resource available Springer Science and Business Media B.V. Relation A related resource ISSN: 25112104; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online