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VISUAL
2000
Springer
13 years 9 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 3 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 6 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»
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
ICIP
2000
IEEE
14 years 6 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