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» Phoneme recognition using Boosted Binary Features
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ICASSP
2009
IEEE
13 years 7 months ago
Volterra series for analyzing MLP based phoneme posterior estimator
We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. Th...
Joel Pinto, Garimella S. V. S. Sivaram, Hynek Herm...
ICIP
2006
IEEE
14 years 11 months ago
Facial Expression Recognition using Advanced Local Binary Patterns, Tsallis Entropies and Global Appearance Features
This paper proposes a novel facial expression recognition approach based on two sets of features extracted from the face images: texture features and global appearance features. T...
Shu Liao, Wei Fan, Albert C. S. Chung, Dit-Yan Yeu...
FGR
2006
IEEE
131views Biometrics» more  FGR 2006»
14 years 4 months ago
Haar Features for FACS AU Recognition
We examined the effectiveness of using Haar features and the Adaboost boosting algorithm for FACS action unit (AU) recognition. We evaluated both recognition accuracy and processi...
Jacob Whitehill, Christian W. Omlin
NIPS
1994
13 years 11 months ago
SARDNET: A Self-Organizing Feature Map for Sequences
A self-organizing neural network for sequence classification called SARDNET is described and analyzed experimentally. SARDNET extends the Kohonen Feature Map architecture with act...
Daniel L. James, Risto Miikkulainen
ICASSP
2008
IEEE
14 years 4 months ago
Discriminative feature selection for hidden Markov models using Segmental Boosting
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...
Pei Yin, Irfan A. Essa, Thad Starner, James M. Reh...