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» Learning Fast Classifiers for Image Spam
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MCS
2005
Springer
13 years 11 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
ECCV
2008
Springer
14 years 7 months ago
Keypoint Signatures for Fast Learning and Recognition
Abstract. Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the ...
Michael Calonder, Vincent Lepetit, Pascal Fua
ICCV
2009
IEEE
13 years 3 months ago
Learning image similarity from Flickr groups using Stochastic Intersection Kernel MAchines
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...
Gang Wang, Derek Hoiem, David A. Forsyth
MM
2010
ACM
174views Multimedia» more  MM 2010»
13 years 6 months ago
Image classification using the web graph
Image classification is a well-studied and hard problem in computer vision. We extend a proven solution for classifying web spam to handle images. We exploit the link structure of...
Dhruv Kumar Mahajan, Malcolm Slaney
ECCV
2006
Springer
14 years 7 months ago
Learning to Detect Objects of Many Classes Using Binary Classifiers
Viola and Jones [VJ] demonstrate that cascade classification methods can successfully detect objects belonging to a single class, such as faces. Detecting and identifying objects t...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei...