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SPEECH
1998
171views more  SPEECH 1998»
14 years 11 months ago
Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...
Nagendra Kumar, Andreas G. Andreou
NIPS
2008
15 years 1 months ago
Dimensionality Reduction for Data in Multiple Feature Representations
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
PAMI
2007
154views more  PAMI 2007»
14 years 11 months ago
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
—Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory—has been designed to provide different soluti...
Shuicheng Yan, Dong Xu, Benyu Zhang, HongJiang Zha...
ECCV
2008
Springer
16 years 1 months ago
A Fast Algorithm for Creating a Compact and Discriminative Visual Codebook
In patch-based object recognition, using a compact visual codebook can boost computational efficiency and reduce memory cost. Nevertheless, compared with a large-sized codebook, it...
Lei Wang, Luping Zhou, Chunhua Shen
102
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ICPR
2008
IEEE
15 years 6 months ago
An evaluation of bi-modal facial appearance+facial expression face biometrics
This paper introduces a framework that employs the Fisher linear discriminant model (FLDM) and classifier (FLDC) on integrated facial appearance and facial expression features. T...
Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz, Tony Ja...