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» Relevance Feedback in Content-based Image Search
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ICCV
2011
IEEE
13 years 9 months ago
HEAT: Iterative Relevance Feedback with One Million Images
It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hu...
Nicolae Suditu, Francois Fleuret
64
Voted
JMLR
2010
127views more  JMLR 2010»
14 years 4 months ago
Content-based Image Retrieval with Multinomial Relevance Feedback
The paper considers an interactive search paradigm in which at each round a user is presented with a set of k images and is required to select one that is closest to her target. P...
Dorota Glowacka, John Shawe-Taylor
TKDE
2008
195views more  TKDE 2008»
14 years 9 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
MM
2006
ACM
164views Multimedia» more  MM 2006»
15 years 3 months ago
Scalable relevance feedback using click-through data for web image retrieval
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...
En Cheng, Feng Jing, Lei Zhang, Hai Jin
ICASSP
2011
IEEE
14 years 1 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