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Semantic Based Image Indexing using Deep Learning

Year: 2024

Type: article

Abstract: This paper introduces a semantic-based image indexing system utilizing a custom Convolutional Neural Network (CNN) for feature extraction and semantic embedding techniques for understanding image content. Traditional image indexing methods rely heavily on low-level visual features, often resulting in inaccurate or irrelevant results. By leveraging deep learning, our proposed system bridges this gap, allowing high-level semantic features to guide indexing and retrieval. Tested on the CIFAR-10 dataset, our approach demonstrates a significant improvement in precision, recall, and overall retrieval performance, showcasing its potential in real-world applications

Source: International Journal of Advanced Research in Science Communication and Technology

DOI: 10.48175/ijarsct-22621

Authors: Drushya Bhaisare, Yash Nakhale, Ridam Lokhande, Sujal Fethfulwar, Aniket Gongle, Dr. Dhananjay Dumbere

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4404995103

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