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Eeg Decoding

EEG Decoding - extracting useful information directly from EEG data.

Papers

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Showing 1–50 of 74 papers

TitleStatusHype
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery ClassificationCode3
CBraMod: A Criss-Cross Brain Foundation Model for EEG DecodingCode3
DBConformer: Dual-Branch Convolutional Transformer for EEG DecodingCode2
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
TCANet: A Temporal Convolutional Attention Network for Motor Imagery EEG DecodingCode1
Subject-Aware Contrastive Learning for BiosignalsCode1
Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge DistillationCode1
ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model InterpretationCode1
MAtt: A Manifold Attention Network for EEG DecodingCode1
MVCNet: Multi-View Contrastive Network for Motor Imagery ClassificationCode1
Transformer-based Spatial-Temporal Feature Learning for EEG DecodingCode1
EEG-CLIP : Learning EEG representations from natural language descriptionsCode1
Time-space-frequency feature Fusion for 3-channel motor imagery classificationCode1
fMRI from EEG is only Deep Learning away: the use of interpretable DL to unravel EEG-fMRI relationshipsCode1
Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample VicinityCode1
Weight Freezing: A Regularization Approach for Fully Connected Layers with an Application in EEG ClassificationCode1
Deep learning with convolutional neural networks for EEG decoding and visualizationCode1
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
EEG decoding with conditional identification information—0
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding—0
EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters—0
EEG-ReMinD: Enhancing Neurodegenerative EEG Decoding through Self-Supervised State Reconstruction-Primed Riemannian Dynamics—0
Evaluating the structure of cognitive tasks with transfer learning—0
Explain EEG-based End-to-end Deep Learning Models in the Frequency Domain—0
Federated deep transfer learning for EEG decoding using multiple BCI tasks—0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network—0
Functional Graph Contrastive Learning of Hyperscanning EEG Reveals Emotional Contagion Evoked by Stereotype-Based Stressors—0
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding—0
Improving EEG Decoding via Clustering-based Multi-task Feature Learning—0
Anchored-STFT and GNAA: An extension of STFT in conjunction with an adversarial data augmentation technique for the decoding of neural signals—0
Independent Feature Enhanced Crossmodal Fusion for Match-Mismatch Classification of Speech Stimulus and EEG Response—0
Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI—0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding—0
Latent Alignment with Deep Set EEG Decoders—0
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification—0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
Passenger hazard perception based on EEG signals for highly automated driving vehicles—0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge—0
The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks—0
A Decomposition-Based Hybrid Ensemble CNN Framework for Driver Fatigue Recognition—0
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding—0
A large-scale evaluation framework for EEG deep learning architectures—0
An amplitudes-perturbation data augmentation method in convolutional neural networks for EEG decoding—0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding—0
Beware of Overestimated Decoding Performance Arising from Temporal Autocorrelations in Electroencephalogram Signals—0
Boosted Convolutional Neural Networks for Motor Imagery EEG Decoding with Multiwavelet-based Time-Frequency Conditional Granger Causality Analysis—0
CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction—0
Combining Euclidean Alignment and Data Augmentation for BCI decoding—0
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BEIRAPearson Correlation0.44—Unverified