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ECCV
2004
Springer
15 years 2 days ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
ADMA
2006
Springer
167views Data Mining» more  ADMA 2006»
14 years 4 months ago
A Correlation Approach for Automatic Image Annotation
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
David R. Hardoon, Craig Saunders, Sándor Sz...
HUMO
2000
Springer
14 years 1 months ago
Specialized Mappings and the Estimation of Human Body Pose from a Single Image
We present an approach for recovering articulated body pose from single monocular images using the Specialized Mappings Architecture (SMA), a non-linear supervised learning archit...
Rómer Rosales, Stan Sclaroff
ICML
2010
IEEE
13 years 11 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
JMLR
2008
188views more  JMLR 2008»
13 years 9 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani