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» Training of Classifiers Using Virtual Samples Only
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SIGIR
2008
ACM
13 years 7 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
ICCS
2009
Springer
13 years 5 months ago
Bending Virtual Spring-Damper: A Solution to Improve Local Platoon Control
This article presents a local control approach to linear vehicle platooning. Linear platoon systems are sets of vehicles that use local or global perception capabilities to form a ...
Jean-Michel Contet, Franck Gechter, Pablo Gruer, A...
ECCV
2004
Springer
14 years 9 months ago
On the Significance of Real-World Conditions for Material Classification
Classifying materials from their appearance is a challenging problem, especially if illumination and pose conditions are permitted to change: highlights and shadows caused by 3D st...
Eric Hayman, Barbara Caputo, Mario Fritz, Jan-Olof...
CVPR
2009
IEEE
1356views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Average of Synthetic Exact Filters
This paper introduces a class of correlation filters called Average of Synthetic Exact Filters (ASEF). For ASEF, the correlation output is completely specified for each training ...
Bruce A. Draper, David S. Bolme, J. Ross Beveridge
BMCBI
2008
142views more  BMCBI 2008»
13 years 7 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...