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» Feature Learning for Recognition with Bayesian Networks
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NIPS
2000
13 years 9 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
ACMSE
2006
ACM
13 years 9 months ago
Hybrid intelligent systems for network security
Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportu...
J. Lane Thames, Randal Abler, Ashraf Saad
ICANN
2003
Springer
14 years 26 days ago
Neural Network Ensemble with Negatively Correlated Features for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it ex...
Hong-Hee Won, Sung-Bae Cho
ICARCV
2008
IEEE
222views Robotics» more  ICARCV 2008»
14 years 2 months ago
Robust fusion using boosting and transduction for component-based face recognition
—Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is...
Fayin Li, Harry Wechsler, Massimo Tistarelli
TASLP
2008
115views more  TASLP 2008»
13 years 7 months ago
Recognition of Dialogue Acts in Multiparty Meetings Using a Switching DBN
Abstract--This paper is concerned with the automatic recognition of dialogue acts (DAs) in multiparty conversational speech. We present a joint generative model for DA recognition ...
Alfred Dielmann, Steve Renals