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» Using hidden Markov models and wavelets for face recognition
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INTERSPEECH
2010
14 years 4 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»
15 years 1 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
15 years 2 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»
15 years 3 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
14 years 10 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