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» Recognition Model with Extension Fields
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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
ICIP
2010
IEEE
13 years 5 months ago
3D augmented Markov random field for object recognition
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...
ICIP
2001
IEEE
14 years 9 months ago
A comparison of discrete and continuous output modeling techniques for a pseudo-2D hidden Markov model face recognition system
Face recognition has become an important topic within the field of pattern recognition and computer vision. In this field a number of different approaches to feature extraction, m...
Frank Wallhoff, Stefan Eickeler, Gerhard Rigoll
ICASSP
2010
IEEE
13 years 7 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
AIPR
2004
IEEE
13 years 11 months ago
An Image Retrieval System Using Multispectral Random Field Models, Color, and Geometric Features
This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves...
Orlando J. Hernandez, Alireza Khotanzad