In this article, behaviour of students in the e-learning environment is analyzed. The novel
pipeline is proposed based on video facial processing. At first, face detection, tracking and …

In this paper, the multi-task learning of lightweight convolutional neural networks is studied
for face identification and classification of facial attributes (age, gender, ethnicity) trained on …

In the last few years, the multi-modal emotion recognition has become an important research
issue in the affective computing community due to its wide range of applications that include …

Automatic emotion recognition (ER) has recently gained much interest due to its potential in
many real-world applications. In this context, multimodal approaches have been shown to …

Multimodal analysis has recently drawn much interest in affective computing, since it can
improve the overall accuracy of emotion recognition over isolated uni-modal approaches …

Emotion recognition in conversations (ERC), the task of recognizing the emotion of each
utterance in a conversation, is crucial for building empathetic machines. Existing studies …

Aspect-based multimodal sentiment analysis (ABMSA) is an important branch of multimodal
sentiment analysis. The goal of ABMSA is to use multimodal information to infer users' …

Multimodal transfer learning aims to transform pretrained representations of diverse
modalities into a common domain space for effective multimodal fusion. However …

With the advancement of artificial intelligence (AI) technology, group-level emotion
recognition (GER) has emerged as an important area in analyzing human behavior. Early …

Multimodal emotion recognition has immense potential for the comprehensive assessment
of human emotions, utilizing multiple modalities that often exhibit complementary …