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» Hierarchical mixture models: a probabilistic analysis
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MLDM
2005
Springer
14 years 1 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
MVA
2006
205views Computer Vision» more  MVA 2006»
13 years 7 months ago
Ontological inference for image and video analysis
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
Christopher Town
PRL
2006
119views more  PRL 2006»
13 years 7 months ago
Exploring the use of latent topical information for statistical Chinese spoken document retrieval
Information retrieval which aims to provide people with easy access to all kinds of information is now becoming more and more emphasized. However, most approaches to information r...
Berlin Chen
ICMLA
2009
13 years 5 months ago
Regularizing the Local Similarity Discriminant Analysis Classifier
Abstract--We investigate parameter-based and distributionbased approaches to regularizing the generative, similarity-based classifier called local similarity discriminant analysis ...
Luca Cazzanti, Maya R. Gupta
IJCV
2008
151views more  IJCV 2008»
13 years 7 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...