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85
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ICCV
2009
IEEE
16 years 4 months ago
Evaluating Information Contributions of Bottom-up and Top-down Processes
This paper presents a method to quantitatively evaluate information contributions of individual bottom-up and topdown computing processes in object recognition. Our objective is...
Xiong Yang, Tianfu Wu, Song-Chun Zhu
88
Voted
NIPS
2008
15 years 1 months ago
Syntactic Topic Models
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Jordan L. Boyd-Graber, David M. Blei
97
Voted
FGR
2008
IEEE
198views Biometrics» more  FGR 2008»
15 years 6 months ago
Recognizing hand gestures using dynamic Bayesian network
In this paper, we describe a dynamic Bayesian network or DBN based approach to both two-hand gestures and onehand gestures. Unlike wired glove-based approaches, the success of cam...
Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee
BICA
2010
14 years 6 months ago
Validating a High Level Behavioral Representation Language (HERBAL): A Docking Study for ACT-R
We present a docking study for Herbal, a high-level behavioral representation language based on the problem space computational model. This study docks an ACT-R model created with ...
Changkun Zhao, Jaehyon Paik, Jonathan H. Morgan, F...
IJCAI
2003
15 years 1 months ago
Bayesian Information Extraction Network
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Leonid Peshkin, Avi Pfeffer