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Chapter and Conference Paper
Distributed Deep Learning for Content-Based Image Retrieval
In content-based image retrieval (CBIR), the main objective is to obtain the best possible feature of an image. Traditionally, color, texture and shape were used to extract the features of image. But as the de...
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Chapter and Conference Paper
Content-Based Image Retrieval Using Energy-Based Frequency Domain Features
Content-Based Image Retrieval (CBIR) has become one of the trending areas of research in computer vision. In traditional CBIR, the features in a spatial domain, such as color, texture, shape, and point feature...
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Article
Content-based image retrieval using Group Normalized-Inception-Darknet-53
In recent days' research, deep learning methods have shown promising performance in various fields of computer vision, including content-based image retrieval (CBIR). In this paper, an improved version of Dark...
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Chapter and Conference Paper
Content-Based Image Retrieval Using Statistical Color Occurrence Feature on Multiresolution Dataset
In modern life, the increasing use of different image-taking devices made image acquisition no longer a difficult task. To access a huge quantity of images having different resolutions stored in the dataset, t...