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» Learning Models for Object Recognition
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ECOOPW
1999
Springer
15 years 7 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 7 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»
15 years 9 months 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 7 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 5 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...