On general purpose time series similarity measures and their use as kernel functions in support vector machines

2014 ◽  
Vol 281 ◽  
pp. 478-495 ◽  
Author(s):  
Helmuth Pree ◽  
Benjamin Herwig ◽  
Thiemo Gruber ◽  
Bernhard Sick ◽  
Klaus David ◽  
...  
Keyword(s):  
Time Series ◽  
Support Vector Machines ◽  
Similarity Measures ◽  
General Purpose ◽  
Kernel Functions ◽  
Support Vector ◽  
Vector Machines

scholarly journals Efficient Technique for Facial Image Recognition With Support Vector Machines in 2D Images With Cross-validation in Matlab

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Support Vector Machines ◽  
Cross Validation ◽  
Facial Recognition ◽  
Kernel Functions ◽  
Efficient Technique ◽  
Support Vector ◽  
Facial Image ◽  
Vector Machines ◽  
Validation Technique ◽  
2D Images

This article presented in the context of 2D global facial recognition, using Gabor Wavelet's feature extraction algorithms, and facial recognition Support Vector Machines (SVM), the latter incorporating the kernel functions: linear, cubic and Gaussian. The models generated by these kernels were validated by the cross validation technique through the Matlab application. The objective is to observe the results of facial recognition in each case. An efficient technique is proposed that includes the mentioned algorithms for a database of 2D images. The technique has been processed in its training and testing phases, for the facial image databases FERET [1] and MUCT [2], and the models generated by the technique allowed to perform the tests, whose results achieved a facial recognition of individuals over 96%.

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