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» Query Decomposition: A Multiple Neighborhood Approach to Rel...
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MMDB
2003
ACM
94views Multimedia» more  MMDB 2003»
13 years 10 months ago
Improving image retrieval effectiveness via multiple queries
Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...
Xiangyu Jin, James C. French
ICASSP
2011
IEEE
12 years 8 months ago
Topic-sensitive interactive image object retrieval with noise-proof relevance feedback
One current direction to enhance the search accuracy in visual object retrieval is to reformulate the original query through (pseudo-)relevance feedback, which augments a query wi...
Jen-Hao Hsiao, Henry Chang
ICIP
2003
IEEE
13 years 10 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...
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
13 years 10 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
ICCV
2003
IEEE
13 years 10 months ago
Reinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...