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SPEECH
1998
171views more  SPEECH 1998»
15 years 5 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 7 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»
15 years 5 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 7 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
ICPR
2008
IEEE
16 years 12 days 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...