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ESOP
2011
Springer
14 years 5 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
ICPR
2008
IEEE
16 years 2 months ago
Learning invariant region descriptor operators with genetic programming and the F-measure
Recognizing and localizing objects is a classical problem in computer vision that is an important stage for many automated systems. In order to perform object recognition many res...
Cynthia B. Pérez, Gustavo Olague
CVPR
2006
IEEE
15 years 7 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou
CVPR
2007
IEEE
16 years 3 months ago
Learning Motion Categories using both Semantic and Structural Information
Current approaches to motion category recognition typically focus on either full spatiotemporal volume analysis (holistic approach) or analysis of the content of spatiotemporal in...
Shu-Fai Wong, Tae-Kyun Kim, Roberto Cipolla
MM
2005
ACM
139views Multimedia» more  MM 2005»
15 years 7 months ago
Multimodal affect recognition in learning environments
We propose a multi-sensor affect recognition system and evaluate it on the challenging task of classifying interest (or disinterest) in children trying to solve an educational pu...
Ashish Kapoor, Rosalind W. Picard