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Abstract: In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high feature similarities to the query may be very di#erent from the query in terms of semantics. This discrepancy between low-level features and high-level concepts is known as the semantic gap. This paper introduces a novel image retrieval scheme, CLUster-based rEtrieval of images by unsupervised learning (CLUE), which... (Update)
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BibTeX entry: (Update)
Y. Chen, J. Z. Wang, and R. Krovetz. CLUE: Cluster-based retrieval of images by unsupervised learning. IEEE Transactions on Image Processing, 14(8):1187--1201, Aug 2005. http://citeseer.ist.psu.edu/chen03clue.html More
@article{ chen04b,
author = {Yixin Chen and James Z. Wang and Robert Krovetz},
title = {CLUE: Cluster-based Retrieval of Images by Unsupervised Learning},
journal = {IEEE Transactions on Image Processing},
year = {2004, in press},
url = {citeseer.ist.psu.edu/chen03clue.html} }
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