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» Using hidden Markov models and wavelets for face recognition
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INTERSPEECH
2010
13 years 2 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng
FGR
2004
IEEE
220views Biometrics» more  FGR 2004»
13 years 11 months ago
Integration of 2D and 3D Images for Enhanced Face Authentication
This paper presents a complete face authentication system integrating 2D intensity and 3D range data, based on a low-cost, real-time structured light sensor. Novel algorithms are ...
Filareti Tsalakanidou, Sotiris Malassiotis, Michae...
SBRN
1998
IEEE
13 years 11 months ago
Design of Radial Basis Function Network as Classifier in Face Recognition Using Eigenfaces
In this paper we investigate alternative designs of a Radial Basis Function Network acting as classifier in a face recognition system. Input to the RBF network is the projections ...
Carlos E. Thomaz, Raul Queiroz Feitosa, Alvaro Vei...
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
ICASSP
2010
IEEE
13 years 7 months ago
Phone recognition using Restricted Boltzmann Machines
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
Abdel-rahman Mohamed, Geoffrey E. Hinton