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» Exploiting Unlabeled Data in Content-Based Image Retrieval
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ICCV
2007
IEEE
14 years 9 months ago
Semi-supervised Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Deng Cai, Xiaofei He, Jiawei Han
ICML
2009
IEEE
14 years 8 months ago
Learning instance specific distances using metric propagation
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised distance metric learning for Collaborative Image Retrieval
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
CVPR
2000
IEEE
14 years 9 months ago
Discriminant-EM Algorithm with Application to Image Retrieval
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
Ying Wu, Qi Tian, Thomas S. Huang