In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …

Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …

Skin cancer affects the lives of millions of people every year, as it is considered the most
popular form of cancer. In the USA alone, approximately three and a half million people are …

Over the past few decades, interest in theories and algorithms for face recognition has been
growing rapidly. Video surveillance, criminal identification, building access control, and …

This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …

Long-short term memory networks (LSTMs), which have recently emerged in sequential data
analysis, are the most widely used type of recurrent neural networks (RNNs) architecture …

Background and objective For diagnosis of arrhythmic heart problems, electrocardiogram
(ECG) signals should be recorded and monitored. The long-term signal records obtained …

In this paper, we propose a deep Recurrent Neural Networks (RNNs) based on Gated
Recurrent Unit (GRU) in a bidirectional manner (BGRU) for human identification from …

Remote sensing image scene classification with deep learning (DL) is a rapidly growing
field that has gained significant attention in the past few years. While previous review papers …