Global ETD Search
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Showing 1 to 4 of 4 for “"content-based image retrieval (CBIR) systems"”.
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Investigation of KimiaNet's and DenseNet's deep features in lung cancer subtypes
… One of which is to act as feature extractors for content-based image retrieval (CBIR) systems. Therefore, it is necessary to investigate how these deep features work and attribute these features to histologic patterns. This study showed that the median of deep feature value could serve as a simple …
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A framework for understanding user interaction with content-based image retrieval: model, interface and users
… essential to the communication between users and content-based image retrieval (CBIR) systems. User interaction covers three key elements: an interaction model, an interactive interface and users. The three key elements combine to enable effective interaction to happen. Many studies have …
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Techniques for Content-based Image Characterization in Wavelets Domain
… techniques aiming to improve the performance of content-based image retrieval (CBIR) systems in wavelets domain using texture analysis. Attention was drawn on CBIR in transform domain and in particular wavelets because of the excellent characteristics for compression and texture extraction …
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Perceived features and similarity of images: An investigation into their relationships and a test of Tversky's contrast model.
… storage, manipulation, and transmission of images have become less costly and more efficient. Consequently, the numbers of images and their users are growing rapidly. This poses challenges to those who organize and provide access to them. One of these challenges is similarity matching. Most …