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» Textural Features and Relevance Feedback for Image Retrieval
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PRL
2000
104views more  PRL 2000»
14 years 11 months ago
PicSOM - content-based image retrieval with self-organizing maps
We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing...
Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkk...
BMVC
2001
15 years 2 months ago
CBIR with Perceptual Region Features
A perceptual approach to generating features for use in indexing and retrieving images is described. Salient regions that immediately attract the eye are colour (textured) regions...
Majid Mirmehdi, Radhakrishnan Periasamy
115
Voted
VIP
2003
15 years 1 months ago
Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the ...
Jing Xin, Jesse S. Jin
ETRA
2010
ACM
176views Biometrics» more  ETRA 2010»
15 years 6 months ago
Learning relevant eye movement feature spaces across users
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
MLDM
1999
Springer
15 years 3 months ago
Independent Feature Analysis for Image Retrieval
Content-based image retrieval methods based on the Euclidean metric expect the feature space to be isotropic. They su€er from unequal di€erential relevance of features in comput...
Jing Peng, Bir Bhanu