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» Feature Combination and Relevance Feedback for 3D Model Retr...
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ESWA
2008
127views more  ESWA 2008»
13 years 5 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...
ICDE
2006
IEEE
191views Database» more  ICDE 2006»
14 years 6 months ago
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Kien A. Hua, Ning Yu, Danzhou Liu
WWW
2008
ACM
14 years 6 months ago
Contextual advertising by combining relevance with click feedback
Contextual advertising supports much of the Web's ecosystem today. User experience and revenue (shared by the site publisher ad the ad network) depend on the relevance of the...
Deepayan Chakrabarti, Deepak Agarwal, Vanja Josifo...
ICITA
2005
IEEE
13 years 11 months ago
Combining Diversity-Based Active Learning with Discriminant Analysis in Image Retrieval
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
DASFAA
2007
IEEE
141views Database» more  DASFAA 2007»
13 years 11 months ago
Integrating Similarity Retrieval and Skyline Exploration Via Relevance Feedback
Similarity retrieval have been widely used in many practical search applications. A similarity query model can be viewed as a logical combination of a set of similarity predicates....
Yiming Ma, Sharad Mehrotra