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Utilizing Query-Adaptive Attention Mechanisms in Deep Learning for Content-Based Image Retrieval

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Keywords:
—Content-based Image Retrieval (CBIR), Querysensitive Attention Mechanisms, Conditional Attention Network (CANet), Co-attention, Feature Extraction, Local Feature Selection, Clustering, Image Retrieval Performance, Convolutional Neural Network (CNN), Many-to-Many Local Feature Matching, Binary Encoding, Benchmark Datasets.

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Kunal1 , Shiwali Yadav1 , Hardik1 , Jatin Bansal2 , Chanchal Rai1 , Aaryan Aneja1
» doi: 10.48047/ecb/2023.12.1025

Abstract

This research paper delves into the domain of Contentbased Image Retrieval (CBIR) by introducing innovative querysensitive attention mechanisms to augment the process of feature extraction for image retrieval

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Volume -12, issue-10 (2023 )
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