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» Optimal feature selection for support vector machines
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ESANN
2008
13 years 9 months ago
GeoKernels: modeling of spatial data on geomanifolds
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
Alexei Pozdnoukhov, Mikhail F. Kanevski
ICIP
2003
IEEE
14 years 9 months ago
Histogram intersection kernel for image classification
In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning pa...
Annalisa Barla, Francesca Odone, Alessandro Verri
CORR
2010
Springer
104views Education» more  CORR 2010»
13 years 8 months ago
Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kant...
CIKM
2009
Springer
13 years 12 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
ICPR
2010
IEEE
13 years 5 months ago
Low-Level Image Segmentation Based Scene Classification
This paper is aimed at evaluating the semantic information content of multiscale, low-level image segmentation. As a method of doing this, we use selected features of segmentation...
Emre Akbas, Narendra Ahuja