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ICITA
2005
IEEE
14 years 2 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...
PRL
2008
143views more  PRL 2008»
13 years 8 months ago
An active feedback framework for image retrieval
In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). Since users are usually unwilling to prov...
Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang...
ICCV
2003
IEEE
14 years 1 months ago
Reinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
ICMCS
2005
IEEE
114views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Self Configurable Queries for Digital Image Libraries
Since multimedia information is characterized by motley types of media with different properties, multimedia content retrieval in digital libraries requires dynamic reconfigurable...
Panagiotis Karagiannis, Nikolaos D. Doulamis, Geor...
ICPR
2004
IEEE
14 years 9 months ago
Group-based Relevance Feedback with Support Vector Machine Ensembles
Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedbac...
Chu-Hong Hoi, Michael R. Lyu