[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …
and modalities using questionnaires, physical signals, and physiological signals. Recently …
EEG based emotion recognition: A tutorial and review
Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …
concept in Artificial Intelligence and holds great potential in emotional health care, human …
EEG emotion recognition based on the attention mechanism and pre-trained convolution capsule network
S Liu, Z Wang, Y An, J Zhao, Y Zhao… - Knowledge-Based Systems, 2023 - Elsevier
Given the rapid development of brain–computer interfaces, emotion identification based on
EEG signals has emerged as a new study area with tremendous importance in recent years …
EEG signals has emerged as a new study area with tremendous importance in recent years …
Emotion recognition in EEG signals using deep learning methods: A review
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 …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Measuring and computing cognitive statuses of construction workers based on electroencephalogram: a critical review
Construction workers' cognitive statuses affecting their safety and productivity are essential
for successful construction management. Electroencephalogram (EEG) provides a potential …
for successful construction management. Electroencephalogram (EEG) provides a potential …
Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition
EEG signals have been reported to be informative and reliable for emotion recognition in
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …
Emotion recognition from EEG based on multi-task learning with capsule network and attention mechanism
Deep learning (DL) technologies have recently shown great potential in emotion recognition
based on electroencephalography (EEG). However, existing DL-based EEG emotion …
based on electroencephalography (EEG). However, existing DL-based EEG emotion …
TC-Net: A Transformer Capsule Network for EEG-based emotion recognition
Deep learning has recently achieved remarkable success in emotion recognition based on
Electroencephalogram (EEG), in which convolutional neural networks (CNNs) are the mostly …
Electroencephalogram (EEG), in which convolutional neural networks (CNNs) are the mostly …
[HTML][HTML] Emotion recognition based on EEG feature maps through deep learning network
A Topic, M Russo - Engineering Science and Technology, an International …, 2021 - Elsevier
Emotion recognition using electroencephalogram (EEG) signals is getting more and more
attention in recent years. Since the EEG signals are noisy, non-linear and have non …
attention in recent years. Since the EEG signals are noisy, non-linear and have non …
Transformers for EEG-based emotion recognition: A hierarchical spatial information learning model
The spatial information of Electroencephalography (EEG) is essential for emotion
recognition model to learn discriminative feature. The convolutional networks and recurrent …
recognition model to learn discriminative feature. The convolutional networks and recurrent …