Abstract
This paper presents the results of a comparative study of linear and kernel-based methods for face recognition. We focus mainly on the experimental comparison of classification methods, i.e. Nearest Neighbor, Linear Support Vector Machine, Kernel based Nearest Neighbor and Nonlinear Support Vector Machine. Some interesting conclusions can be obtained after all of these methods are performed on two well-known database, i.e. ORL, YALE Face Database, respectively.
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Lu, C., Zhang, T., Zhang, W., Yang, G. (2005). An Experimental Evaluation of Linear and Kernel-Based Classifiers for Face Recognition. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_21
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DOI: https://doi.org/10.1007/11427445_21
Publisher Name: Springer, Berlin, Heidelberg
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