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Enhancing cross-modal retrieval via label graph optimization and hybrid loss functions. [PDF]
Sci RepWang L, Wang C, Peng S.
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Ensemble-based high-performance deep learning models for medical image retrieval in breast cancer detection. [PDF]
Sci RepFawzy AE +3 more
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Localized content based image retrieval
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, 2005We define localized content-based image retrieval as a CBIR task where the user is only interested in a portion of the image, and the rest of the image is irrelevant. In this paper we present a localized CBIR system, Accio, that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and ...
Rouhollah, Rahmani +4 more
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Faceted Content-Based Image Retrieval
2008 19th International Conference on Database and Expert Systems Applications, 2008In typical content-based image retrieval systems it is not possible to navigate the image space by simultaneously applying multiple similarity criteria. The model we propose addresses this problem by representing the search for the images similar to a given image as the exploration of a lattice of (non-disjoint) image clusters, induced by a natural ...
Amato G, Meghini C
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2009
Content-Based Image Retrieval (CBIR) aims to search images that are perceptually similar to the querybased on visual content of the images without the help of annotations. The current CBIR systems use global features (e.g., color, texture, and shape) as image descriptors, or usefeatures extracted from segmented regions (called region-based descriptors).
Ming Zhang, Reda Alhajj
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Content-Based Image Retrieval (CBIR) aims to search images that are perceptually similar to the querybased on visual content of the images without the help of annotations. The current CBIR systems use global features (e.g., color, texture, and shape) as image descriptors, or usefeatures extracted from segmented regions (called region-based descriptors).
Ming Zhang, Reda Alhajj
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Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, 2005
The last decade has witnessed great interest in research on content-based image retrieval. This has paved the way for a large number of new techniques and systems, and a growing interest in associated fields to support such systems. Likewise, digital imagery has expanded its horizon in many directions, resulting in an explosion in the volume of image ...
Ritendra Datta, Jia Li, James Z. Wang
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The last decade has witnessed great interest in research on content-based image retrieval. This has paved the way for a large number of new techniques and systems, and a growing interest in associated fields to support such systems. Likewise, digital imagery has expanded its horizon in many directions, resulting in an explosion in the volume of image ...
Ritendra Datta, Jia Li, James Z. Wang
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2008 6th International Symposium on Intelligent Systems and Informatics, 2008
A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases.
Igor Marinovic, Igor Furstner
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A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases.
Igor Marinovic, Igor Furstner
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Content-Based Image Retrieval in Astronomy
Information Retrieval, 2000Summary: Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information should be summarized and indexed for this specific kind of images.
Csillaghy, A. +2 more
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