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Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples
(Springer, 2022-03)
Deep neural network (DNN) architectures are considered to be robust to random perturbations. Nevertheless, it was shown that they could be severely vulnerable to slight but carefully crafted perturbations of the input, ...
TENET: a new hybrid network architecture for adversarial defense
(Springer Science and Business Media Deutschland GmbH, 2023-08)
Deep neural network (DNN) models are widely renowned for their resistance to random perturbations. However, researchers have found out that these models are indeed extremely vulnerable to deliberately crafted and seemingly ...
Convolutional neural network (CNN) algorithm based facial emotion recognition (FER) system for FER-2013 dataset
(IEEE, 2022-11-18)
Facial expression recognition (FER) is the key to understanding human emotions and feelings. It is an active area of research since human thoughts can be collected, processed, and used in customer satisfaction, politics, ...
Recovery of impenetrable rough surface profiles via CNN-based deep learning architecture
(Taylor and Francis Ltd., 2022-08-18)
In this paper, a convolutional neural network (CNN)-based deep learning (DL) architecture for the solution of an electromagnetic inverse problem related to imaging of the shape of the perfectly electric conducting (PEC) ...