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TREC
2008
13 years 6 months ago
DUTIR at TREC 2008 Blog Track
For opinion finding task our method of the combination of 5 Windows method and Pseudo Relevance Feedback behaves well, achieving an improvement of over 20% on the baseline adhoc r...
Jianmei Chen, Wei Guo, Fengming Pan, Fuyang Chang,...
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 9 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
ACCV
2006
Springer
13 years 11 months ago
Heuristic Pre-clustering Relevance Feedback in Region-Based Image Retrieval
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of contentbased image retrieval (CBIR) systems. In this paper...
Wan-Ting Su, Wen-Sheng Chu, James Jenn-Jier Lien
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...
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...