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ICIP
2002
IEEE
13 years 9 months ago
A graphic-theoretic model for incremental relevance feedback in image retrieval
Many traditional relevance feedback approaches for CBIR can only achieve limited short-term performance improvement without benefiting long-term performance. To remedy this limita...
Yueting Zhuang, Jun Yang 0003, Qing Li, Yunhe Pan
MM
2004
ACM
248views Multimedia» more  MM 2004»
13 years 9 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
VIP
2003
13 years 5 months ago
Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the ...
Jing Xin, Jesse S. Jin
ICPR
2000
IEEE
13 years 8 months ago
Integrating Unlabeled Images for Image Retrieval Based on Relevance Feedback
Retrieval techniques based on pure similarity metrics are often suffered from the scales of image features. An alternative approach is to learn a mapping based on queries and rele...
Ying Wu, Qi Tian, Thomas S. Huang
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
13 years 8 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