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» Learning Mid-Level Features For Recognition
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ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
14 years 1 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ECML
1993
Springer
13 years 11 months ago
Exploiting Context When Learning to Classify
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the t...
Peter D. Turney
ICARCV
2008
IEEE
222views Robotics» more  ICARCV 2008»
14 years 2 months ago
Robust fusion using boosting and transduction for component-based face recognition
—Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is...
Fayin Li, Harry Wechsler, Massimo Tistarelli
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
14 years 2 months ago
Towards robust place recognition for robot localization
— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of hi...
Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara C...
AIRS
2004
Springer
14 years 1 months ago
Automatic Word Clustering for Text Categorization Using Global Information
This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Wenliang Chen, Xingzhi Chang, Huizhen Wang, Jingbo...