[HTML][HTML] Interactive multi-agent convolutional broad learning system for EEG emotion recognition
S Shi, W Liu - Expert Systems with Applications, 2025 - Elsevier
Electroencephalogram (EEG) emotion recognition is gaining significance in intelligent
human–computer interaction. Multi-agent learning can capture more complete and reliable …
human–computer interaction. Multi-agent learning can capture more complete and reliable …
ERTNet: an interpretable transformer-based framework for EEG emotion recognition
Background Emotion recognition using EEG signals enables clinicians to assess patients'
emotional states with precision and immediacy. However, the complexity of EEG signal data …
emotional states with precision and immediacy. However, the complexity of EEG signal data …
Exploring CEEMDAN and LMD domains entropy features for decoding EEG-based emotion patterns
Electroencephalogram (EEG) signal-based emotion classification is vital in the ever-growing
human-computer interface (HCI) applications. However, the chaotic, non-stationary, and …
human-computer interface (HCI) applications. However, the chaotic, non-stationary, and …
MES-CTNet: A Novel Capsule Transformer Network Base on a Multi-Domain Feature Map for Electroencephalogram-Based Emotion Recognition
Y Du, H Ding, M Wu, F Chen, Z Cai - Brain Sciences, 2024 - mdpi.com
Emotion recognition using the electroencephalogram (EEG) has garnered significant
attention within the realm of human–computer interaction due to the wealth of genuine …
attention within the realm of human–computer interaction due to the wealth of genuine …
Set-pMAE: spatial-spEctral-temporal based parallel masked autoEncoder for EEG emotion recognition
C Pan, H Lu, C Lin, Z Zhong, B Liu - Cognitive Neurodynamics, 2024 - Springer
The utilization of Electroencephalography (EEG) for emotion recognition has emerged as
the primary tool in the field of affective computing. Traditional supervised learning methods …
the primary tool in the field of affective computing. Traditional supervised learning methods …
Advanced functional connectivity analysis with integrated EEG signal enhancement and GTW-EEG-GAN for emotion detection
NV Babu, EGM Kanaga - International Journal of Computers and …, 2024 - Taylor & Francis
Emotion recognition is crucial in human-computer interaction and psychological research,
utilizing modalities such as facial expressions, voice intonations, and EEG signals. This …
utilizing modalities such as facial expressions, voice intonations, and EEG signals. This …
Decoding emotional patterns using NIG modeling of EEG signals in the CEEMDAN domain
Electroencephalogram (EEG) signals used for emotion classification are vital in the Human–
Computer Interface (HCI), which has gained a lot of focus. However, the irregular and non …
Computer Interface (HCI), which has gained a lot of focus. However, the irregular and non …
Emotion Recognition in EEG Based on Multilevel Multidomain Feature Fusion
ZL Li, H Cao, JS Zhang - IEEE Access, 2024 - ieeexplore.ieee.org
In emotion recognition tasks, electroencephalography (EEG) has gained significant favor
among researchers as a powerful biological signal tool. However, existing studies often fail …
among researchers as a powerful biological signal tool. However, existing studies often fail …
Eeg Emotion Recognition Based on Efficient-Capsule Network with Convolutional Attention
W Tang, LF Fan, YF Gu - Xue fen and Gu, Yi Fan, Eeg Emotion … - papers.ssrn.com
EEG-based emotion recognition, as a pivotal component in human-computer interaction,
has garnered considerable scholarly interest. And finding EEG features with stronger time …
has garnered considerable scholarly interest. And finding EEG features with stronger time …