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106
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FGR
1998
IEEE
170views Biometrics» more  FGR 1998»
15 years 5 months ago
Feature-Point Tracking by Optical Flow Discriminates Subtle Differences in Facial Expression
Current approaches to automated analysis have focused on a small set of prototypic expressions (e.g., joy or anger). Prototypic expressions occur infrequently in everyday life, ho...
Jeffrey F. Cohn, Adena J. Zlochower, James Jenn-Ji...
95
Voted
PRIS
2004
15 years 2 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...
96
Voted
ICPR
2008
IEEE
16 years 1 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...
147
Voted
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
15 years 2 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
83
Voted
SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
15 years 2 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