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VISUAL
2000
Springer
14 years 1 months ago
Content-Based Image Retrieval by Relevance Feedback
Relevance feedback is a powerful technique for content-based image retrieval. Many parameter estimation approaches have been proposed for relevance feedback. However, most of them ...
Zhong Jin, Irwin King, Xuequn Li
ICCV
2009
IEEE
13 years 7 months ago
A multi-sample, multi-tree approach to bag-of-words image representation for image retrieval
The state-of-the-art content based image retrieval sys
Zhong Wu, Qifa Ke, Jian Sun, Heung-Yeung Shum
ICIP
1999
IEEE
14 years 11 months ago
A Neural Network Approach to Interactive Content-Based Retrieval of Video Databases
A neural network scheme is presented in this paper for adaptive video indexing and retrieval. First, a limited but characteristic amount of frames are extracted from each video sc...
Nikolaos D. Doulamis, Anastasios D. Doulamis, Stef...
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
14 years 2 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
ICIP
2000
IEEE
14 years 11 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang