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AMR
2007
Springer
171views Multimedia» more  AMR 2007»
13 years 10 months ago
Automatic Image Annotation with Relevance Feedback and Latent Semantic Analysis
The goal of this paper is to study the image-concept relationship as it pertains to image annotation. We demonstrate how automatic annotation of images can be implemented on partia...
Donn Morrison, Stéphane Marchand-Maillet, E...
ICCV
2003
IEEE
13 years 9 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
2005
IEEE
14 years 6 months ago
Semantic kernel learning for interactive image retrieval
Content-based image retrieval systems still have difficulties to bridge the semantic gap between the low-level representation of images and the high level concepts the user is loo...
Philippe Henri Gosselin, Matthieu Cord
ICIP
2008
IEEE
14 years 6 months ago
Long term learning for image retrieval over networks
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
David Picard, Arnaud Revel, Matthieu Cord
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 8 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