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- W2359597686 abstract "Face image feature parameter was extracted by using K-L transform,then SVM was employed as face identification.The kernel function is the core of the SVM,and different kernel function will produce different classification effect.In order to get kernel function with good learning ability and generalization ability,and according to the properties,kernel function will be local kernel function and global kernel function is linear combination into a new kernel function-combined-kernel function.It used Cross-Validation method to optimize its parameters and combination coefficients.We applied the kernel in SVM and compared the common kernel in YALE face library and the ORL face database recognition experiment.The simulation results verify the effectiveness of the kernel function.Experimental results certify that the combined-kernel function of SVM is superior to common kernel function of SVM." @default.
- W2359597686 created "2016-06-24" @default.
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- W2359597686 date "2013-01-01" @default.
- W2359597686 modified "2023-09-24" @default.
- W2359597686 title "Face Recognition Based on Combined-Kernel Function of Support Vector Machine" @default.
- W2359597686 hasPublicationYear "2013" @default.
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