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» Content-Based Image Retrieval by Relevance Feedback
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MM
2006
ACM
164views Multimedia» more  MM 2006»
14 years 1 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
ESWA
2008
127views more  ESWA 2008»
13 years 7 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...
MM
2004
ACM
129views Multimedia» more  MM 2004»
14 years 29 days ago
A novel log-based relevance feedback technique in content-based image retrieval
Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic g...
Chu-Hong Hoi, Michael R. Lyu
JMLR
2010
127views more  JMLR 2010»
13 years 2 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
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
14 years 1 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...