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 …

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 …

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 …

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

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 …

Although tremendous strides have been made in facial expression recognition (FER),
recognizing facial expressions in non-frontal views remains an open challenge due to the …