[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
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 …
A comprehensive survey on emotion recognition based on electroencephalograph (EEG) signals
K Kamble, J Sengupta - Multimedia Tools and Applications, 2023 - Springer
Emotion recognition using electroencephalography (EEG) is becoming an interesting topic
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
PrimePatNet87: prime pattern and tunable q-factor wavelet transform techniques for automated accurate EEG emotion recognition
Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
EEG-based emotion recognition using spatial-temporal graph convolutional LSTM with attention mechanism
L Feng, C Cheng, M Zhao, H Deng… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
The dynamic uncertain relationship among each brain region is a necessary factor that limits
EEG-based emotion recognition. It is a thought-provoking problem to availably employ time …
EEG-based emotion recognition. It is a thought-provoking problem to availably employ time …
GLFANet: A global to local feature aggregation network for EEG emotion recognition
Recently, emotion recognition technology based on electroencephalogram (EEG) signals is
widely used in areas such as human–computer interaction and disease diagnosis …
widely used in areas such as human–computer interaction and disease diagnosis …
[HTML][HTML] A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence
Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
Cross-cultural emotion recognition with EEG and eye movement signals based on multiple stacked broad learning system
With increasing social globalization, interaction between people from different cultures has
become more frequent. However, there are significant differences in the expression and …
become more frequent. However, there are significant differences in the expression and …
A multi-dimensional graph convolution network for EEG emotion recognition
Due to the changeable, high-dimensional, nonstationary, and other characteristics of
electroencephalography (EEG) signals, the recognition of EEG signals is mostly limited to …
electroencephalography (EEG) signals, the recognition of EEG signals is mostly limited to …
EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning
Electroencephalogram (EEG) based emotion classification reflects the actual and intrinsic
emotional state, resulting in more reliable, natural, and meaningful human-computer …
emotional state, resulting in more reliable, natural, and meaningful human-computer …