Results 301 to 310 of about 6,693,779 (355)
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2010
CLEF was the first benchmarking campaign that organized an evaluation event for image retrieval: the ImageCLEF photographic ad hoc retrieval task in 2003. Since then, this task has become one of the most popular tasks of ImageCLEF, providing both the resources and a framework necessary to carry out comparative laboratory–style evaluation of multi ...
Monica Lestari Paramita +1 more
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CLEF was the first benchmarking campaign that organized an evaluation event for image retrieval: the ImageCLEF photographic ad hoc retrieval task in 2003. Since then, this task has become one of the most popular tasks of ImageCLEF, providing both the resources and a framework necessary to carry out comparative laboratory–style evaluation of multi ...
Monica Lestari Paramita +1 more
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2008 19th International Conference on Pattern Recognition, 2008
Image retrieval has been receiving increasing interest due to the vast amount of images publicly available on the Internet. Most image sharing sites, such as FlickR, allow for text/tag-based image searching. In the research community, content-based image retrieval has been under investigation since the early 1990s.
Henning Mueller, Thomas Deselaers
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Image retrieval has been receiving increasing interest due to the vast amount of images publicly available on the Internet. Most image sharing sites, such as FlickR, allow for text/tag-based image searching. In the research community, content-based image retrieval has been under investigation since the early 1990s.
Henning Mueller, Thomas Deselaers
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Privacy-Preserving Image Retrieval for Medical IoT Systems: A Blockchain-Based Approach
IEEE Network, 2019With the advent of medical IoT devices, the types and volumes of medical images have significantly increased. Retrieving of medical images is of great importance to facilitate disease diagnosis and improve treatment efficiency.
Meng Shen +4 more
semanticscholar +1 more source
2013
Sometimes we have only an image that we should get our information by that. There are many search engines and software's that can search images but all of them don’t have the ability to search for similar images, image search by image. In this paper first, we explained performance, algorithmic search, and retrieval power of 2 powerful search engines ...
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Sometimes we have only an image that we should get our information by that. There are many search engines and software's that can search images but all of them don’t have the ability to search for similar images, image search by image. In this paper first, we explained performance, algorithmic search, and retrieval power of 2 powerful search engines ...
openaire +1 more source
Journal of Visual Languages & Computing, 1997
Abstract Most image-retrieval systems rely on similarity measures for collecting images of similar types. Similarity measures are an integral part in the development of image management systems. In this paper, we propose frame-based similarity measures for accessing structured images, e.g.
ZHI-QIANG LIU, JOANNE PING SUN
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Abstract Most image-retrieval systems rely on similarity measures for collecting images of similar types. Similarity measures are an integral part in the development of image management systems. In this paper, we propose frame-based similarity measures for accessing structured images, e.g.
ZHI-QIANG LIU, JOANNE PING SUN
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Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
Content-based image retrieval relies on low-level image features such as color, texture and segmentation. Humans, however, search for images by their cognitive, deep meaning content. This paper introduces an approach and an algorithm for cognitive image retrieval. Each image is indexed by a visual object-process diagram (VOPD) that represents the image
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Content-based image retrieval relies on low-level image features such as color, texture and segmentation. Humans, however, search for images by their cognitive, deep meaning content. This paper introduces an approach and an algorithm for cognitive image retrieval. Each image is indexed by a visual object-process diagram (VOPD) that represents the image
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2011
This chapter presents search methods for image retrieval which are boosted using the user’s supervision by means of the human–computer interaction methodology. Two contributions are presented which cover different aspects of this problem.
Alejandro Héctor Toselli +2 more
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This chapter presents search methods for image retrieval which are boosted using the user’s supervision by means of the human–computer interaction methodology. Two contributions are presented which cover different aspects of this problem.
Alejandro Héctor Toselli +2 more
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RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
Medical Image Anal., 2022Xiyue Wang +8 more
semanticscholar +1 more source
2011
With the rapid increase in the amount of registered trademarks around the world, trademark image retrieval has been developed to deal with a vast amount of trademark images in a trademark registration system. Many different approaches have been developed throughout these years in an attempt to develop an effective TIR system.
Wing-Yin Chau, Chia-Hung Wei, Yue Li
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With the rapid increase in the amount of registered trademarks around the world, trademark image retrieval has been developed to deal with a vast amount of trademark images in a trademark registration system. Many different approaches have been developed throughout these years in an attempt to develop an effective TIR system.
Wing-Yin Chau, Chia-Hung Wei, Yue Li
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2006
This paper addresses the problem of texture retrieval by using a perceptual approach based on multiple viewpoints. We use a set of features that have a perceptual meaning corresponding to human visual perception. These features are estimated using a set of computational features that can be based on two viewpoints: the original images viewpoint and the
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This paper addresses the problem of texture retrieval by using a perceptual approach based on multiple viewpoints. We use a set of features that have a perceptual meaning corresponding to human visual perception. These features are estimated using a set of computational features that can be based on two viewpoints: the original images viewpoint and the
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