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Facial attributes are emerging soft biometrics that have the potential to reject non-matches, for example, based on mismatching gender. To be usable in stand-alone systems, facial attributes must be extracted from images automatically and reliably. In this paper, we propose a simple yet effective solution for automatic facial attribute extraction by training a deep convolutional neural network (DCNN)...
Machine learning models are vulnerable to adversarial examples formed by applying small carefully chosen perturbations to inputs that cause unexpected classification errors. In this paper, we perform experiments on various adversarial example generation approaches with multiple deep convolutional neural networks including Residual Networks, the best performing models on ImageNet Large-Scale Visual...
As biometric authentication systems become common in everyday use, researchers are beginning to address privacy issues in biometric recognition. With the growing use of mobile devices, it is important to develop approaches that support remote mobile verification. This paper outlines the need for a mobile/remote SVM-based authentication system that does not compromise the privacy of the subject being...
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