CONTENT-BASED IMAGE RETRIEVAL USING DEEP FEATURE EXTRACTION AND SIMILARITY MEASURES
Keywords:
Content-Based Image Retrieval, Deep Learning, CNN, Feature Extraction, Similarity Measures, Image Processing.Abstract
Content-Based Image Retrieval (CBIR) has become animportant research area due to the rapid growth of digital image
collections in fields such as medical imaging, security systems,multimedia databases, and social media platforms. Traditional image
retrieval methods rely on textual annotations
References
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2008). Image retrieval: Ideas, influences, and trends. ACM Computing Surveys, 40(2), 1–60.
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Published
2023-12-05
How to Cite
Dr. Mallika Jain. (2023). CONTENT-BASED IMAGE RETRIEVAL USING DEEP FEATURE EXTRACTION AND SIMILARITY MEASURES. Journal of Computational Analysis and Applications (JoCAAA), 31(4), 2650–2658. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5115
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