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ICIP
2000
IEEE
14 years 7 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
SPIESR
1998
195views Database» more  SPIESR 1998»
13 years 7 months ago
Relevance Feedback Techniques in Interactive Content-Based Image Retrieval
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...
Yong Rui, Thomas S. Huang, Sharad Mehrotra
ICCV
2007
IEEE
14 years 8 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 6 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung
EDBT
2006
ACM
172views Database» more  EDBT 2006»
14 years 6 months ago
Fast Query Point Movement Techniques with Relevance Feedback for Content-Based Image Retrieval
Abstract. Target search in content-based image retrieval (CBIR) systems refers to finding a specific (target) image such as a particular registered logo or a specific historical ph...
Danzhou Liu, Kien A. Hua, Khanh Vu, Ning Yu