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» Using Component Features for Face Recognition
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ICPR
2008
IEEE
15 years 9 months ago
Transductive optimal component analysis
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Yuhua Zhu, Yiming Wu, Xiuwen Liu, Washington Mio
JMLR
2010
155views more  JMLR 2010»
14 years 9 months ago
Structured Sparse Principal Component Analysis
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
Rodolphe Jenatton, Guillaume Obozinski, Francis Ba...
156
Voted
ICMI
2003
Springer
184views Biometrics» more  ICMI 2003»
15 years 7 months ago
Real time facial expression recognition in video using support vector machines
Enabling computer systems to recognize facial expressions and infer emotions from them in real time presents a challenging research topic. In this paper, we present a real time ap...
Philipp Michel, Rana El Kaliouby
ICASSP
2010
IEEE
15 years 2 months ago
Comparison of modulation features for phoneme recognition
In this paper, we compare several approaches for the extraction of modulation frequency features from speech signal using a phoneme recognition system. The general framework in th...
Sriram Ganapathy, Samuel Thomas, Hynek Hermansky
ICPR
2006
IEEE
15 years 8 months ago
Fast Feature Extraction Approach for Multi-Dimension Feature Space Problems
Recently, we proposed a fast feature extraction approach denoted FSOM utilizes Self Organizing Map (SOM). FSOM [1] overcomes the slowness of traditional SOM search algorithm. We i...
Alaa El. Sagheer, Naoyuki Tsuruta, Rin-ichiro Tani...