Content-based image retrieval with fuzzy clustering for feature vector normalization

Vu, Van-Hieu

doi:10.1007/s11042-023-15215-1

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Cited by 3 publications

References 48 publications

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Semantic deep learning and adaptive clustering for handling multimodal multimedia information retrieval

Sattari,

Yazici

2024

Multimed Tools Appl

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Semantic deep learning and adaptive clustering for handling multimodal multimedia information retrieval

Sattari,

Yazici

2024

Multimed Tools Appl

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An Effective Clustering Using Moth Flame Optimization for Content-Based Image Retrieval

Aluvala,

Abed Almoussawi,

Almusawi

et al. 2023

2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC)

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T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

Thanikachalam,

Thavasimuthu,

Arulkumar

et al. 2024

Preprint

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In the field of Image Mining (IM) and Content-Based Image Retrieval (CBIR), the significance lies in extracting meaningful information from visual data. By focusing on the intrinsic meaning within images, semantic features enhance the accuracy and relevance of image retrieval systems, bridging the gap between human understanding and computational analysis in visual data exploration. This research explores the fusion of image processing techniques and CBIR. The need for this research is based on the persistent challenges in existing CBIR systems, where traditional methods often fall short of comprehensively capturing the intricate semantics of images. The primary objective of this research is to propose a novel approach to CBIR by implementing the Tokens-to-Token Vision Transformer (T2T-ViT) to address the limitations of traditional CBIR systems and enhance the accuracy and relevance of image retrieval. The T2T-ViT model achieves exceptional performance in CBIR on Corel datasets, with a high accuracy of 99.42%, precision of 98.66%, recall of 98.89%, and F-measure of 99.35%. The model demonstrates a harmonious balance between identifying and retrieving relevant images compared to existing models.

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Content-based image retrieval with fuzzy clustering for feature vector normalization

Cited by 3 publications

References 48 publications

Semantic deep learning and adaptive clustering for handling multimodal multimedia information retrieval

Semantic deep learning and adaptive clustering for handling multimodal multimedia information retrieval

An Effective Clustering Using Moth Flame Optimization for Content-Based Image Retrieval

T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

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