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PRIS
2004
13 years 11 months ago
Effect of Feature Smoothing Methods in Text Classification Tasks
Abstract. The number of features to be considered in a text classification system is given by the size of the vocabulary and this is normally in the range of the tens or hundreds o...
David Vilar, Hermann Ney, Alfons Juan, Enrique Vid...
ICMCS
2009
IEEE
215views Multimedia» more  ICMCS 2009»
13 years 7 months ago
Image trimming via saliency region detection and iterative feature matching
Detection of saliency regions in images is useful for object based image understanding and object localization. In our work, we investigate a saliency region detection algorithm b...
Jiawei Huang, Ze-Nian Li
ICPR
2008
IEEE
14 years 10 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
13 years 11 months ago
Co-selection of Features and Instances for Unsupervised Rare Category Analysis
Rare category analysis is of key importance both in theory and in practice. Previous research work focuses on supervised rare category analysis, such as rare category detection an...
Jingrui He, Jaime G. Carbonell