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IJNCR
2010
59views more  IJNCR 2010»
14 years 8 months ago
Cognitively Inspired Neural Network for Recognition of Situations
we present a cognitively inspired mathematical learning framework called Neural Modeling Fields (NMF). We apply it to learning and recognition of situations composed of objects. NM...
Roman Ilin, Leonid I. Perlovsky
CSIE
2009
IEEE
15 years 5 months ago
Discriminative Random Fields for Behavior Modeling
This paper proposed an approach of human behavior modeling based on Discriminative Random Fields. In this model, by introducing the hidden behavior feature functions and time wind...
Tianyu Huang, Chongde Shi, Fengxia Li
GBRPR
2009
Springer
15 years 5 months ago
A Graph Based Data Model for Graphics Interpretation
A universal data model, named DG, is introduced to handle vectorized data uniformly during the whole recognition process. The model supports low level graph algorithms as well as h...
Endre Katona
ACL
2004
15 years 13 days ago
Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins, Mark...
ECCV
1994
Springer
15 years 3 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li