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» Face Detection and Recognition using Hidden Markov Models
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ICIP
2009
IEEE
15 years 10 months ago
Facial Marks: Soft Biometric For Face Recognition
We propose to utilize micro features, namely facial marks (e.g., freckles, moles, and scars) to improve face recognition and retrieval performance. Facial marks can be used in thr...
PERVASIVE
2004
Springer
15 years 3 months ago
Recognizing Workshop Activity Using Body Worn Microphones and Accelerometers
Most gesture recognition systems analyze gestures intended for communication (e.g. sign language) or for command (e.g. navigation in a virtual world). We attempt instead to recogn...
Paul Lukowicz, Jamie A. Ward, Holger Junker, Mathi...
DAGM
2003
Springer
15 years 3 months ago
Improving Children's Speech Recognition by HMM Interpolation with an Adults' Speech Recognizer
In this paper we address the problem of building a good speech recognizer if there is only a small amount of training data available. The acoustic models can be improved by interpo...
Stefan Steidl, Georg Stemmer, Christian Hacker, El...
BMCBI
2007
104views more  BMCBI 2007»
14 years 9 months ago
A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and de
Background: Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoin...
Oscar M. Rueda, Ramón Díaz-Uriarte
CSL
2002
Springer
14 years 9 months ago
Transformation streams and the HMM error model
The most popular model used in automatic speech recognition is the hidden Markov model (HMM). Though good performance has been obtained with such models there are well known limit...
M. J. F. Gales