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ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
13 years 11 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang
ICMCS
2006
IEEE
127views Multimedia» more  ICMCS 2006»
14 years 1 months ago
An Interactive Region-Based Image Clustering and Retrieval Platform
Content-based Image retrieval has become an important part of information retrieval technology. Images can be viewed as high dimensional data and are usually represented by their ...
Ying Liu, Xin Chen, Chengcui Zhang, Alan P. Spragu...
BMVC
2010
13 years 5 months ago
Trans Media Relevance Feedback for Image Autoannotation
Automatic image annotation is an important tool for keyword-based image retrieval, providing a textual index for non-annotated images. Many image auto annotation methods are based...
Thomas Mensink, Jakob J. Verbeek, Gabriela Csurka
CIVR
2006
Springer
181views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Image Searching and Browsing by Active Aspect-Based Relevance Learning
Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning...
Mark J. Huiskes
CISST
2004
164views Hardware» more  CISST 2004»
13 years 8 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp