85 search results - page 11 / 17 » Aggregating Learned Probabilistic Beliefs |
105
Voted
CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
SIGIR
2012
ACM
12 years 12 months ago
2012
ACM
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
99
Voted
ICPR
2008
IEEE
2008
IEEE
Weakly supervised learning using proportion-based information: An application to fisheries acoustics
15 years 10 months ago
This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
111
Voted
ML
2008
ACM
14 years 9 months ago
2008
ACM
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
90
Voted
EMMCVPR
2005
Springer
15 years 3 months ago
2005
Springer
This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...