ItemArticle

A novel deep learning based multimedia video retrieval framework using may fly optimization

Title
A novel deep learning based multimedia video retrieval framework using may fly optimization
Creator
Kaushik, Ruchi; Pradeep, S.; Shanbhog, Manjula; Tamizhselvi, A.; Jagdale, Jayashree; Mahajan, Rashima
Description
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.
Source
International Journal of Information Technology (Singapore);
Date
01-01-2025
Publisher
Springer Science and Business Media B.V.
Subject
Efficient net; Histogram equalization; May fly optimization (MFO); Multimedia; Video retrieval
Coverage
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
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 25112104;
Format
online
Language
English
Type
Article

Citation

Kaushik, Ruchi; Pradeep, S.; Shanbhog, Manjula; Tamizhselvi, A.; Jagdale, Jayashree; Mahajan, Rashima, “A novel deep learning based multimedia video retrieval framework using may fly optimization,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/22100.

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