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ISCIS
2009
Springer
14 years 1 months ago
Dynamic feature weights with relevance feedback in content-based image retrieval
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...
Esin Guldogan, Moncef Gabbouj
ICIP
2010
IEEE
13 years 4 months ago
Image retrieval with feature selection and relevance feedback
This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from...
Yu Sun, Bir Bhanu
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 15 days ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
ICMCS
2005
IEEE
134views Multimedia» more  ICMCS 2005»
14 years 15 days ago
Relevance Feedback Methods in Content Based Retrieval and Video Summarization
In the current state-of-the-art in multimedia content analysis (MCA), the fundamental techniques are typically derived from core pattern recognition and computer vision algorithms...
Micha Haas, Ard Oerlemans, Michael S. Lew
ICDE
2006
IEEE
191views Database» more  ICDE 2006»
14 years 8 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