Probabilistic feature relevance learning for content-based image retrieval

J Peng, B Bhanu, S Qing - Computer vision and image understanding, 1999 - Elsevier
Most of the current image retrieval systems use “one-shot” queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …
被引用次数：196 相关文章

Probabilistic Feature Relevance Learning for Content-Based Image Retrieval

J Peng, B Bhanu, S Qing - Computer Vision and Image Understanding, 1999 - infona.pl
Most of the current image retrieval systems use “one-shot” queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …

[引用][C] Probabilistic feature relevance learning for content-based image retrieval

J PENG, BIR BHANU, S QING - Computer vision and image …, 1999 - pascal-francis.inist.fr
Probabilistic feature relevance learning for content-based image retrieval CNRS Inist Pascal-Francis
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Probabilistic Feature Relevance Learning for Content-Based Image Retrieval

J Peng, B Bhanu, S Qing - Computer Vision and Image Understanding, 1999 - dl.acm.org
Most of the current image retrieval systems use “one-shot” queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …
[PDF] ucr.edu

[PDF][PDF] Probabilistic Feature Relevance Learning for Content-Based Image Retrieval

J Peng, B Bhanu, S Qing - 1999 - vislab.ucr.edu
Most of the current image retrieval systems use “one-shot” queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …

Probabilistic feature relevance learning for content-based image retrieval

J Peng, B Bhanu, S Qing - Computer Vision and Image …, 1999 - researchwith.montclair.edu
Most of the current image retrieval systems useone-shot'queries to a database to retrieve
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Probabilistic Feature Relevance Learning for Content-Based Image Retrieval

J Peng, B Bhanu, S Qing - 1999 - digitalcommons.montclair.edu
Most of the current image retrieval systems useone-shot'queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …
[PDF] psu.edu

[PDF][PDF] Probabilistic Feature Relevance Learning for Content-Based Image Retrieval

J Peng, B Bhanu, S Qing - 1999 - Citeseer
Most of the current image retrieval systems use “one-shot” queries to a database to retrieve
similar images. Typically a K-nearest neighbor kind of algorithm is used, where weights …

[引用][C] Probabilistic feature relevance learining for content-based image retrieval

J Peng, B Bhanu, S Qing - Computer Vision and Image Understanding, 1999 - dl.acm.org
Probabilistic feature relevance learining for content-based image retrieval | Computer Vision
and Image Understanding skip to main content ACM Digital Library home ACM home Google …

[引用][C] Probabilistic feature relevance learning for content-based image retrieval

J PENG, BIR BHANU, S QING - Computer vision and image understanding, 1999 - Elsevier