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ICPR
2006
IEEE
14 years 3 months ago
Fast Linear Discriminant Analysis Using Binary Bases
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...
Feng Tang, Hai Tao
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
13 years 10 months ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...
ICASSP
2008
IEEE
14 years 3 months ago
Ultrasonic Doppler sensor for speaker recognition
In this paper we present a novel use of an acoustic Doppler sonar for multi-modal speaker identification. An ultrasonic emitter directs a 40kHz tone toward the speaker. Reflecti...
Kaustubh Kalgaonkar, Bhiksha Raj
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
14 years 25 days ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
FGR
2008
IEEE
214views Biometrics» more  FGR 2008»
14 years 3 months ago
Normalized LDA for semi-supervised learning
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Bin Fan, Zhen Lei, Stan Z. Li