Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …

Emotion recognition based on electroencephalography (EEG) is a significant task in the
brain-computer interface field. Recently, many deep learning-based emotion recognition …

Multimodal signals are powerful for emotion recognition since they can represent emotions
comprehensively. In this article, we compare the recognition performance and robustness of …

Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

Affecting computing is an artificial intelligence area of study that recognizes, interprets,
processes, and simulates human affects. The user's emotional states can be sensed through …

Transfer learning (TL) utilizes data or knowledge from one or more source domains to
facilitate learning in a target domain. It is particularly useful when the target domain has very …

In this paper, we present a multimodal emotion recognition framework called EmotionMeter
that combines brain waves and eye movements. To increase the feasibility and wearability …

Emotions have an important role in daily life, not only in human interaction, but also in
decision-making processes, and in the perception of the world around us. Due to the recent …