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» Learning Models for Object Recognition
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ECOOPW
1999
Springer
15 years 11 months ago
Deriving Object-Oriented Frameworks from Domain Knowledge
Although a considerable number of successful frameworks have been developed during the last decade, designing a high-quality framework is still a difficult task. Generally, it is ...
Mehmet Aksit
COLT
1994
Springer
15 years 11 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
ICMCS
2005
IEEE
110views Multimedia» more  ICMCS 2005»
16 years 22 days ago
Learned color constancy from local correspondences
The ability of humans for color constancy, i.e. the ability to correct for color deviation caused by a different illumination, is far beyond computer vision performances: nowadays...
Tijmen Moerland, Frédéric Jurie
AC
2000
Springer
15 years 11 months ago
Graph-Theoretical Methods in Computer Vision
The management of large databases of hierarchical (e.g., multi-scale or multilevel) image features is a common problem in object recognition. Such structures are often represented ...
Ali Shokoufandeh, Sven J. Dickinson
CVPR
2003
IEEE
16 years 9 months ago
Video-Based Face Recognition Using Probabilistic Appearance Manifolds
This paper presents a novel method to model and recognize human faces in video sequences. Each registered person is represented by a low-dimensional appearance manifold in the amb...
Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David...