With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Emotional expressions are the behaviors that communicate our emotional state or attitude to
others. They are expressed through verbal and non-verbal communication. Complex human …

Facial expression recognition has been an active area of research over the past few
decades, and it is still challenging due to the high intra-class variation. Traditional …

Facial emotion recognition (FER) is significant for human-computer interaction such as
clinical practice and behavioral description. Accurate and robust FER by computer models …

Facial expression recognition (FER) is to separate the specific expression state from the
given static image or video to determine the psychological emotions of the recognized …

Affective computing has been largely limited in terms of available data resources. The need
to collect and annotate diverse in-the-wild datasets has become apparent with the rise of …

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is
still challenging due to intra-class variations and inter-class similarities in facial images …

In this paper we propose an implement a general convolutional neural network (CNN)
building framework for designing real-time CNNs. We validate our models by creating a real …

Automatic facial expression recognition (FER) has gained much attention due to its
applications in human-computer interaction. Among the approaches to improve FER tasks …

Current artificial intelligence systems for determining a person's emotions rely heavily on lip
and mouth movement and other facial features such as eyebrows, eyes, and the forehead …