Facial expression recognition is a hot research topic and can be applied in many computer
vision fields, such as human–computer interaction, affective computing and so on. In this …

Affective computing stands at the forefront of artificial intelligence (AI), seeking to imbue
machines with the ability to comprehend and respond to human emotions. Central to this …

The use of machine learning algorithms for facial expression recognition and patient
monitoring is a growing area of research interest. In this study, we present a technique for …

Over the past decades, researches on facial expression recognition have been restricted
within six basic expressions (anger, fear, disgust, happiness, sadness and surprise) …

Facial expression methods play a vital role in human–computer interaction and other fields,
but there are factors such as occlusion, illumination, and pose changes in wild facial …

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

Automated human emotion recognition from facial expressions is a well-studied problem
and still remains a very challenging task. Some efficient or accurate deep learning models …

In this paper, a novel Monogenic Sobel Directional Pattern (MSDP) using fractional order
masks is proposed for extracting features. The MSDP uses fractional-order Sobel masks to …

Facial expression recognition (FER) is a widely used technique for emotion recognition. In
recent years, numerous deep convolutional neural network (CNN) models have been …

Detecting and recognizing facial emotions from human facial movements is one of the most
important research area in human-computer interaction. In this paper, a saliency map and …