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» Feature Selection for Support Vector Machines
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ICPR
2004
IEEE
14 years 8 months ago
Corner Detection Using Support Vector Machines
A support vector machine based algorithm for corner detection is presented. It is based on computing the direction of maximum gray-level change for each edge pixel in an image, an...
Malay K. Kundu, Minakshi Banerjee, Pabitra Mitra
JRTIP
2008
151views more  JRTIP 2008»
13 years 6 months ago
Automatic gender recognition based on pixel-pattern-based texture feature
A pixel-pattern-based texture feature (PPBTF) is proposed for real-time gender recognition. A gray-scale image is transformed into a pattern map where edges and lines are to be use...
Huchuan Lu, Yingjie Huang, Yen-Wei Chen, Deli Yang
AINA
2007
IEEE
14 years 2 months ago
Detecting Coordinated Distributed Multiple Attacks
This paper describes results concerning the robustness and generalization capabilities of kernel methods in detecting coordinated distributed multiple attacks (CDMA) using network...
Srinivas Mukkamala, Krishna Yendrapalli, Ram B. Ba...
IJCNN
2006
IEEE
14 years 1 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
14 years 8 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...