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Hierarchical Adaptive Masking Graph Convolutional Network for Eeg-Based Emotion Classification

https://doi.org/10.2139/ssrn.5381613
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inferredcites →https://doi.org/10.1007/s11571-020-09634-1openalex-snapshot
EEG-based emotion recognition using 4D convolutional recurrent neural network
inferredcites →https://doi.org/10.1007/s11571-023-10004-wopenalex-snapshot
EEG-based emotion recognition using a temporal-difference minimizing neural network
inferredcites →https://doi.org/10.1016/j.bspc.2023.105744openalex-snapshot
EEG decoding for musical emotion with functional connectivity features
inferredcites →https://doi.org/10.1016/j.eswa.2024.126028openalex-snapshot
Domain adversarial learning with multiple adversarial tasks for EEG emotion recognition
inferredcites →https://doi.org/10.1016/j.knosys.2022.109038openalex-snapshot
Affect recognition from scalp-EEG using channel-wise encoder networks coupled with geometric deep learning and multi-channel feature fusion
inferredcites →https://doi.org/10.1016/j.neuron.2011.09.006openalex-snapshot
Functional Network Organization of the Human Brain
inferredcites →https://doi.org/10.1016/j.patcog.2017.12.002openalex-snapshot
Deep Convolutional Neural Networks for mental load classification based on EEG data
inferredcites →https://doi.org/10.1088/1741-2552/abca18openalex-snapshot
Uncovering the structure of clinical EEG signals with self-supervised learning
inferredcites →https://doi.org/10.1109/jbhi.2024.3443651openalex-snapshot
GMAEEG: A Self-Supervised Graph Masked Autoencoder for EEG Representation Learning
inferredcites →https://doi.org/10.1109/jbhi.2024.3504604openalex-snapshot
EEG-Deformer: A Dense Convolutional Transformer for Brain-Computer Interfaces
inferredcites →https://doi.org/10.1109/jiot.2023.3281911openalex-snapshot
Dynamic Convolution With Multilevel Attention for EEG-Based Motor Imagery Decoding
inferredcites →https://doi.org/10.1109/taffc.2017.2712143openalex-snapshot
Identifying Stable Patterns over Time for Emotion Recognition from EEG
inferredcites →https://doi.org/10.1109/taffc.2017.2768030openalex-snapshot
Emotion Recognition Based on High-Resolution EEG Recordings and Reconstructed Brain Sources
inferredcites →https://doi.org/10.1109/taffc.2018.2817622openalex-snapshot
EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/taffc.2018.2885474openalex-snapshot
A Bi-Hemisphere Domain Adversarial Neural Network Model for EEG Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2019.2937768openalex-snapshot
GCB-Net: Graph Convolutional Broad Network and Its Application in Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2020.2994159openalex-snapshot
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
inferredcites →https://doi.org/10.1109/taffc.2020.3013711openalex-snapshot
An Efficient LSTM Network for Emotion Recognition From Multichannel EEG Signals
inferredcites →https://doi.org/10.1109/taffc.2021.3051332openalex-snapshot
SparseDGCNN: Recognizing Emotion From Multichannel EEG Signals
inferredcites →https://doi.org/10.1109/taffc.2021.3064940openalex-snapshot
Variational Instance-Adaptive Graph for EEG Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2021.3068496openalex-snapshot
EEG Feature Selection via Global Redundancy Minimization for Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2022.3170428openalex-snapshot
GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2023.3288885openalex-snapshot
Fine-Grained Interpretability for EEG Emotion Recognition: Concat-Aided Grad-CAM and Systematic Brain Functional Network
inferredcites →https://doi.org/10.1109/taffc.2024.3394436openalex-snapshot
Spectral-Spatial Attention Alignment for Multi-Source Domain Adaptation in EEG-Based Emotion Recognition
inferredcites →https://doi.org/10.1109/taffc.2024.3433613openalex-snapshot
Grop: Graph Orthogonal Purification Network for EEG Emotion Recognition
inferredcites →https://doi.org/10.1109/tamd.2015.2431497openalex-snapshot
Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks
inferredcites →https://doi.org/10.1109/tbme.2019.2897651openalex-snapshot
EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations
inferredcites →https://doi.org/10.1109/tcds.2020.2999337openalex-snapshot
A Novel Bi-Hemispheric Discrepancy Model for EEG Emotion Recognition
inferredcites →https://doi.org/10.1109/tim.2025.3551490openalex-snapshot
Improved EEGNet With a Multilevel Spatial Feature Extraction Module for EEG Decoding
inferredcites →https://doi.org/10.1109/tnnls.2022.3225855openalex-snapshot
Hierarchical Dynamic Graph Convolutional Network With Interpretability for EEG-Based Emotion Recognition
inferredcites →https://doi.org/10.1111/j.1748-1716.1957.tb01396.xopenalex-snapshot
Volume Conduction of the Spike of‘ the Motor Unit Potential Investigated with a New Type of Multielectrode
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