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 …

Abstract Machine learning has profoundly transformed various industries, notably
revolutionizing the retail sector through diverse applications that significantly enhance …

Exploring the objective signals associated with subjective emotional states has practical
significance. Emotional experiences play a fundamental role in people's well-being [1] and …

In recent years, significant advancements have been made in the field of brain–computer
interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The …

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 …

Human-in-the-loop (HITL) frameworks are increasingly recognized for their potential to
improve annotation accuracy in emotion estimation systems by combining machine …

Diffusion models have recently emerged as powerful generative frameworks for producing
high-quality images. A pivotal component of these models is the noise schedule, which …

The chapter delves into the foundations of generative artificial intelligence (AI), offering an
introductory overview and a nuanced understanding of its basic principles, history, and …

In the contemporary media landscape, maintaining emotional authenticity is essential for
television presenters to establish trust and forge meaningful connections with their …

In the realm of EEG-based emotion recognition, individual differences present significant
challenges for cross-subject recognition, making it an essential area of research. While …