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MM
2006
ACM
130views Multimedia» more  MM 2006»
14 years 1 months ago
An unsupervised method for clustering images based on their salient regions of interest
We have developed a biologically-motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual...
Gustavo B. Borba, Humberto R. Gamba, Oge Marques, ...
CVIU
2006
162views more  CVIU 2006»
13 years 7 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
CVPR
2004
IEEE
13 years 11 months ago
Visual Object Categorization Using Distance-Based Discriminant Analysis
This paper formulates the problem of object categorization in the discriminant analysis framework focusing on transforming visual feature data so as to make it conform to the comp...
Serhiy Kosinov, Stéphane Marchand-Maillet, ...
ICDAR
2011
IEEE
12 years 7 months ago
A New Feature Optimization Method Based on Two-Directional 2DLDA for Handwritten Chinese Character Recognition
—LDA transformation is one of the popular feature dimension reduction techniques for the feature extraction in most handwritten Chinese characters recognition systems. The integr...
Xue Gao, Wenhuan Wen, Lianwen Jin