Emotion recognition has attracted major attention in numerous fields because of its relevant
applications in the contemporary world: marketing, psychology, surveillance, and …

With the advancement of human-computer interaction, robotics, and especially humanoid
robots, there is an increasing trend for human-to-human communications over online …

The purposes are to explore the effect of Digital Twins (DTs) in Unmanned Aerial Vehicles
(UAVs) on providing medical resources quickly and accurately during COVID-19 prevention …

We present an approach that combines automatic features learned by convolutional neural
networks (CNN) and handcrafted features computed by the bag-of-visual-words (BOVW) …

An image is worth a thousand words; hence, a face image illustrates extensive details about
the specification, gender, age, and emotional states of mind. Facial expressions play an …

Facial Expression Recognition (FER) is a challenging task that improves natural human-
computer interaction. This paper focuses on automatic FER on a single in-the-wild (ITW) …

Automatic facial expression recognition (FER) is one of the most challenging tasks in
computer vision. FER admits a wide range of applications in human–computer interaction …

The interaction between humans and an NAO robot using deep convolutional neural
networks (CNN) is presented in this paper based on an innovative end-to-end pipeline …

With the advent of deep learning, the research on facial expression recognition (FER) has
received a lot of interest. Different deep convolutional neural network (DCNN) architectures …

In this paper our group proposes and designs a lightweight convolutional neural network
(CNN) for detecting facial emotions in real-time and in bulk to achieve a better classification …