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» Textural Features and Relevance Feedback for Image Retrieval
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ICIP
2003
IEEE
15 years 5 months ago
Evaluating group-based relevance feedback for content-based image retrieval
We have been developing new relevance feedback algorithms for Content-based Image Retrieval (CBIR) that allow the user to achieve more flexible query. In conjunction with the new...
Munehiro Nakazato, Charlie K. Dagli, Thomas S. Hua...
ICIP
2000
IEEE
16 years 1 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
CVPR
2004
IEEE
16 years 1 months ago
Random Sampling Based SVM for Relevance Feedback Image Retrieval
Relevance feedback (RF) schemes based on support vector machine (SVM) have been widely used in content-based image retrieval. However, the performance of SVM based RF is often poo...
Dacheng Tao, Xiaoou Tang
NIPS
2004
15 years 1 months ago
Instance-Based Relevance Feedback for Image Retrieval
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Giorgio Giacinto, Fabio Roli
MM
2004
ACM
248views Multimedia» more  MM 2004»
15 years 5 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