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» Data selection for support vector machine classifiers
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IPCV
2008
14 years 11 months ago
Neonatal Facial Pain Detection Using NNSOA and LSVM
- We report classification experiments using the pilot Infant COPE database of neonatal facial expressions. Two sets of DCT coeffiecents were used to train a neural network simulta...
Sheryl Brahnam, Loris Nanni, Randall S. Sexton
BMEI
2009
IEEE
14 years 11 months ago
Cell Clumping Quantification and Automatic Area Classification in Peripheral Blood Smear Images
Cell enumeration in peripheral blood smears and cell are widely applied in biological and pathological practice. Not every area in the smear is appropriate for enumeration due to ...
Wei Xiong, S. H. Ong, Christina Kang, Joo-Hwee Lim...
KI
2007
Springer
14 years 10 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...
ICDAR
2009
IEEE
14 years 7 months ago
Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers
In recent years research towards Indian handwritten character recognition is getting increasing attention. Many approaches have been proposed by the researchers towards handwritte...
Umapada Pal, Tetsushi Wakabayashi, Fumitaka Kimura
ICPR
2004
IEEE
15 years 11 months ago
An Efficient Three-Stage Classifier for Handwritten Digit Recognition
This paper proposes an efficient three-stage classifier for handwritten digit recognition based on NN (Neural Network) and SVM (Support Vector Machine) classifiers. The classifica...
Dejan Gorgevik, Dusan Cakmakov