Year: 2025
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
Author: Sujal Fethfulwar
Institution: Dr. Babasaheb Ambedkar Technological University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411353048