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ICML
2005
IEEE
15 years 10 days ago
The cross entropy method for classification
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
Shie Mannor, Dori Peleg, Reuven Y. Rubinstein
MICCAI
2002
Springer
15 years 12 days ago
Comparative Exudate Classification Using Support Vector Machines and Neural Networks
After segmenting candidate exudates regions in colour retinal images we present and compare two methods for their classification. The Neural Network based approach performs margina...
Alireza Osareh, Majid Mirmehdi, Barry T. Thomas, R...
ICPR
2000
IEEE
15 years 18 days ago
Feature Selection for Support Vector Machines
Lothar Hermes, Joachim M. Buhmann
ICPR
2004
IEEE
15 years 19 days ago
Statistical Classification of Raw Textile Defects
In this paper, the problem of classification of defects occurring in a textile manufacture is addressed. A new classification scheme is devised in which different features, extrac...
Ivan A. Rossi, Manuele Bicego, Vittorio Murino
ICPR
2006
IEEE
15 years 19 days ago
Enhancing Training Set for Face Detection
We present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. The motivation is from Support Vector Machines (SV...
Ruiping Wang, Jie Chen, Shiguang Shan, Wen Gao
ICIP
2002
IEEE
15 years 1 months ago
Application of support vector machines classifiers to visual speech recognition
In this paper we proposed a visual speech recognition network based on Support Vector Machines. Each word of the dictionary is modeled by a set of temporal sequences of visemes. E...
Mihaela Gordan, Constantine Kotropoulos, Apostolos...
ICIP
2002
IEEE
15 years 1 months ago
On the stability of support vector machines for face detection
Ioan Buciu, Constantine Kotropoulos, Ioannis Pitas
ICIP
2003
IEEE
15 years 1 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