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

Emotion recognition has opened up many challenges, which lead to various advances in
computer vision and artificial intelligence. The rapid development in this field has …

Semantic segmentation of urban scenes is an essential component in various applications
of autonomous driving. It makes great progress with the rise of deep learning technologies …

We present the first study in the literature that has aimed to determine Depression Anxiety
Stress Scale (DASS) levels by analyzing facial expressions using Facial Action Coding …

This paper proposes a new method based on a multiple branch cross-connected
convolutional neural network (MBCC-CNN) for facial expression recognition. Compared with …

Classroom communication involves teacher's behavior and student's responses. Extensive
research has been done on the analysis of student's facial expressions, but the impact of …

Research on facial expression recognition (FER) technology can promote the development
of theoretical and practical applications for our daily life. Currently, most of the related works …

Although a number of researchers consider serious games as effective teaching/learning
tools, the literature is fragmented when it comes to the factors that shape the users' …

This paper is an extension of our previously published ACM Multimedia 2022 paper, which
was ranked 3rd in the macro-expressions (MaEs) and micro-expressions (MEs) spotting task …

In this brief, we consider the problem of descriptors construction for the task of content-based
image retrieval using deep neural networks. The idea of neural codes, based on fully …