One of the most promising techniques used in various sciences is deep neural networks
(DNNs). A special type of DNN called a convolutional neural network (CNN) consists of …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

Abstract Deep Convolutional Neural Networks (CNNs) have been pushing the frontier of
face recognition over past years. However, existing CNN models are far less accurate when …

With the recent advancement of deep convolutional neural networks, significant progress
has been made in general face recognition. However, the state-of-the-art general face …

Convolutional neural network (CNN) based approaches are the state of the art in various
computer vision tasks including face recognition. Considerable research effort is currently …

The limited capacity to recognise faces under occlusions is a long‐standing problem that
presents a unique challenge for face recognition systems and even humans. The problem …

Conventional finger-vein recognition systems perform recognition based on the finger-vein
lines extracted from the input images or image enhancement, and texture feature extraction …

The development of biometric applications, such as facial recognition (FR), has recently
become important in smart cities. Many scientists and engineers around the world have …

Face recognition has the perception of a solved problem, however when tested at the million-
scale exhibits dramatic variation in accuracies across the different algorithms [??]. Are the …