Paper Title
A Deep Convolutional Neural Network with Sharpening Filters for Face Recognition

Abstract
In face recognition problem, human identities can be predicted based on its raw facial features. Traditional approaches for classification are based on statistical approaches dimension reduction, while the neural networks and support vector machines on machine learning. However, the performance using conventional features rises dramatically in complex intra-personal face variations, such as illumination, expression, pose, makeups and occlusions. Therefore, reducing the intrapersonal variations is an eternal topic in face recognition that is crucial matters. This paper proposes a convolutional neural network (CNN) embedded with sharpening filters which can improve the problem. This model can classify an input image into a large number of identity classes, because Sharpening convolutional neural network greatly improve the model generation capacity by introducing effective Sharpening layer. Keywords - Biometric Authentication, Deep Learning, Face Rec-ognition, Deep Convolutional Neural Networks, Sharpening Filter.

Author - Wen-Shiung Chen, Peng-An Chen, Yen-Feng Chen, Lili Hsieh

Published : Volume-6,Issue-1  ( Jan, 2019 )

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