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ICIP
2003
IEEE
14 years 7 months ago
Kernel indexing for relevance feedback image retrieval
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
Jing Peng, Douglas R. Heisterkamp
MM
2009
ACM
221views Multimedia» more  MM 2009»
14 years 23 days ago
Using large-scale web data to facilitate textual query based retrieval of consumer photos
The rapid popularization of digital cameras and mobile phone cameras has lead to an explosive growth of consumer photo collections. In this paper, we present a (quasi) real-time t...
Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo
ERCIMDL
1997
Springer
169views Education» more  ERCIMDL 1997»
13 years 10 months ago
Relevance Feedback and Query Expansion for Searching the Web: A Model for Searching a Digital Library
: A fully operational large scale digital library is likely to be based on a distributed architecture and because of this it is likely that a number of independent search engines m...
Alan F. Smeaton, Francis Crimmins
ICCV
2003
IEEE
13 years 11 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...
ICIP
2001
IEEE
14 years 7 months ago
Category-based image retrieval
This work presents a novel approach to content-based image retrieval in categorical multimedia databases. The images are indexed using a combination of text and content descriptor...
Shawn D. Newsam, Baris Sumengen, B. S. Manjunath