Facial emotional processing is one of the most important activities in effective calculations,
engagement with people and computers, machine vision, video game testing, and consumer …

Facial expression recognition (FER) in the wild is a novel and challenging topic in the field of
human emotion perception. Different kinds of convolutional neural network (CNN) …

Facial expression recognition (FER) is challenging because the appearance of an
expression varies significantly depending on head pose and inter-subject characteristics …

In real-world applications, factors such as head pose variation, occlusion, and poor image
quality make facial expression recognition (FER) an open challenge. In this paper, a novel …

Due to the lack of data available for training, deep learning hardly performed well in the field
of garbage image classification. We choose the TrashNet data set which is widely used in …

Multiview Facial Expression Recognition (MFER) is a well-known interdisciplinary problem
among computer science and related disciplines with promising and valuable applications …

Facial expression is one of the most powerful, natural, and universal signals for human
beings to express emotional states and intentions. There are many applications for facial …

Multi-view facial expression recognition (FER) is a challenging task because the
appearance of an expression varies greatly due to poses. To alleviate the influences of …

Currently, with the rapid development of deep learning, many breakthroughs have been
made in the field of facial expression recognition (FER). However, according to our prior …

In the process of day-to-day learning, expressions are very vital. Detection of human
expressions is growing and has caught the interest of many researchers in the past few …