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NIPS
2000
13 years 9 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
IJCV
2000
136views more  IJCV 2000»
13 years 7 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
CMIG
2010
110views more  CMIG 2010»
13 years 2 months ago
Unsupervised SVM-based gridding for DNA microarray images
This paper presents a novel method for unsupervised DNA microarray gridding based on Support Vector Machines (SVMs). Each spot is a small region on the microarray surface where cha...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
UAI
2000
13 years 9 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
CIVR
2007
Springer
126views Image Analysis» more  CIVR 2007»
14 years 2 months ago
Image annotation: which approach for realistic databases?
This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...
Nicolas Hervé, Nozha Boujemaa