Nonlinear Fuzzy Robust PCA Algorithm for Pain Decision Support System


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This paper describes particular pain events to be located as in infant face images with feature extraction algorithm. Nonlinear Fuzzy Robust PCA (NFRPCA) feature extraction is implemented to test its effectiveness in recognizing pain in images. In this work, two classifiers, Fuzzy k-nearest neighbors (Fuzzy k-NN) and k-nearest neighbors (k-NN) are employed. Result shows that the NFRPCA and classifier (Fuzzy k-NN and k-NN) can be used for the recognition of infant pain images with the best accuracy of 89.77%.



Edited by:

Dashnor Hoxha, Francisco E. Rivera and Ian McAndrew




M. N. Mansor et al., "Nonlinear Fuzzy Robust PCA Algorithm for Pain Decision Support System", Advanced Materials Research, Vol. 1016, pp. 785-789, 2014

Online since:

August 2014




* - Corresponding Author

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