Mammographic image recognition using rough sets and support vector machines

2014 ◽  
Vol 8 ◽  
pp. 1193-1200
Author(s):  
Jiming Lan
Keyword(s):  
Support Vector Machines ◽  
Image Recognition ◽  
Rough Sets ◽  
Support Vector ◽  
Mammographic Image ◽  
Vector Machines

Twin Support Vector Machines Based on Rough Sets

2012 ◽  
Vol 6 (20) ◽  
pp. 493-500 ◽  
Author(s):  
Junzhao Yu ◽  
Shifei Ding ◽  
Fengxiang Jin ◽  
Huajuan Huang ◽  
Youzhen Han
Keyword(s):  
Support Vector Machines ◽  
Rough Sets ◽  
Support Vector ◽  
Twin Support Vector Machines ◽  
Vector Machines

Optimization of Kernel Function Parameters SVM Based on the GA

2012 ◽  
Vol 433-440 ◽  
pp. 4124-4128 ◽  
Author(s):  
Jian Hua Zhang
Keyword(s):  
Support Vector Machines ◽  
Image Recognition ◽  
Kernel Function ◽  
Support Vector ◽  
Vector Machines ◽  
And Performance

That Support Vector Machines applies to image recognition have good results，But the kernel function C and parameters of the SVM which influence the result and performance has not been decided. Against this question, this paper bring forward a new algorithm that combines SVM with GA to classify and uses GA to select excellent kernel function, the results of experiment show Image Recognition based on SVM and GA are effective.

Analysis of EEG Epileptic Signals with Rough Sets and Support Vector Machines

2009 ◽  
pp. 325-334
Author(s):  
Joo-Heon Shin ◽  
Dave Smith ◽  
Roman Swiniarski ◽  
F. Edward Dudek ◽  
Andrew White ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Rough Sets ◽  
Support Vector ◽  
Vector Machines
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