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Many different approaches for content-based image retrieval have been proposed in the literature. Successful approaches consider not only simple features like color, but also take ...
Content-based image retrieval uses features that can be extracted from the images themselves. Using more than one representation of the images in a collection can improve the resu...
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
We propose a neural network based method for organizing images for content-based image retrieval. We use spectral histogram features, the histograms of filtered images to capture...