In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …

Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …

We present an interpretation of Inception modules in convolutional neural networks as being
an intermediate step in-between regular convolution and the depthwise separable …

Lack of transparency in deep neural networks (DNNs) make them susceptible to backdoor
attacks, where hidden associations or triggers override normal classification to produce …

Deep learning-based techniques have achieved state-of-the-art performance on a wide
variety of recognition and classification tasks. However, these networks are typically …

Deep learning-based techniques have achieved state-of-the-art performance on a wide
variety of recognition and classification tasks. However, these networks are typically …

Traditional methods of computer vision and machine learning cannot match human
performance on tasks such as the recognition of handwritten digits or traffic signs. Our …

Abstract Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019
and has spread rapidly all over the world since the beginning of 2020, has infected millions …

The advent of metasurfaces in recent years has ushered in a revolutionary means to
manipulate the behavior of light on the nanoscale. The design of such structures, to date …