Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …

Aiming at the problem that the traditional license plate recognition method lacking of
accuracy and speed, an end-to-end deep learning model for license plate location and …

How to extract discriminative latent feature representations from electroencephalography
(EEG) signals and build a generalized model is a topic in EEG-based emotion recognition …

Electroencephalogram (EEG) is a crucial and widely utilized technique in neuroscience
research. In this paper, we introduce a novel graph neural network called the spatial …

Emotion recognition has attracted attention in recent years. It is widely used in healthcare,
teaching, human-computer interaction, and other fields. Human emotional features are often …

In this study, we conducted a systematic literature review of 107 primary studies conducted
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …

Electroencephalography (EEG) emotion recognition is an important task for brain–computer
interfaces. The time, frequency, and spatial domains of EEG signals have been widely …

Emotion is a human attitude experience and corresponding behavioral response to
objective things. Effective emotion recognition is important for the intelligence and …

With the development of affective computing, discriminative feature selection is critical for
electroencephalography (EEG) emotion recognition. In this article, we fused four EEG …