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» Probabilistic Declarative Information Extraction
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CVPR
2011
IEEE
13 years 3 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
VLDB
2007
ACM
125views Database» more  VLDB 2007»
14 years 1 months ago
Data Integration with Uncertainty
This paper reports our first set of results on managing uncertainty in data integration. We posit that data-integration systems need to handle uncertainty at three levels, and do...
Xin Luna Dong, Alon Y. Halevy, Cong Yu
CVPR
2004
IEEE
14 years 9 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang
EUSAI
2003
Springer
14 years 26 days ago
Vision-Based Localization for Mobile Platforms
In this paper, we describe methods to localize a mobile robot in an indoor environment from visual information. An appearance-based approach is adopted in which the environment is ...
Josep M. Porta, Ben J. A. Kröse
SIGIR
2000
ACM
13 years 12 months ago
OCELOT: a system for summarizing Web pages
Abstract We introduce OCELOT, a prototype system for automatically generating the “gist” of a web page by summarizing it. Although most text summarization research to date has ...
Adam L. Berger, Vibhu O. Mittal