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VISUAL
2000
Springer
13 years 11 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
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
13 years 7 months ago
Content-Based Image Categorization and Retrieval using Neural Networks
We propose a neural network based method for organizing images for content-based image retrieval. We use spectral histogram features, the histograms of filtered images to capture...
Yuhua Zhu, Xiuwen Liu, Washington Mio
CAIVD
1998
182views more  CAIVD 1998»
13 years 9 months ago
Content-Based 3D Neuroradiologic Image Retrieval: Preliminary Results
A content-based 3D neuroradiologic image retrieval system is being developed at the Robotics Institute of CMU. The special characteristics of this system include: 1 directly deali...
Yanxi Liu, William E. Rothfus, Takeo Kanade
ICPR
2004
IEEE
14 years 8 months ago
Entropy-Based Measures for Clustering and SOM Topology Preservation Applied to Content-Based Image Indexing and Retrieval
Content-based image retrieval (CBIR) addresses the problem of finding images relevant to the users' information needs, based principally on low-level visual features for whic...
Markus Koskela, Jorma Laaksonen, Erkki Oja
ICASSP
2007
IEEE
14 years 1 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian