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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
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding—0
DBConformer: Dual-Branch Convolutional Transformer for EEG DecodingCode2
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding—0
TCANet: A Temporal Convolutional Attention Network for Motor Imagery EEG DecodingCode1
ViEEG: Hierarchical Neural Coding with Cross-Modal Progressive Enhancement for EEG-Based Visual Decoding—0
EEG-CLIP : Learning EEG representations from natural language descriptionsCode1
MVCNet: Multi-View Contrastive Network for Motor Imagery ClassificationCode1
Subject Disentanglement Neural Network for Speech Envelope Reconstruction from EEG—0
EEG-ReMinD: Enhancing Neurodegenerative EEG Decoding through Self-Supervised State Reconstruction-Primed Riemannian Dynamics—0
Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI—0
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding—0
CBraMod: A Criss-Cross Brain Foundation Model for EEG DecodingCode3
Towards Scalable Handwriting Communication via EEG Decoding and Latent Embedding Integration—0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge—0
Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model—0
Independent Feature Enhanced Crossmodal Fusion for Match-Mismatch Classification of Speech Stimulus and EEG Response—0
Dual-TSST: A Dual-Branch Temporal-Spectral-Spatial Transformer Model for EEG Decoding—0
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery ClassificationCode3
Passenger hazard perception based on EEG signals for highly automated driving vehicles—0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
Towards Linguistic Neural Representation Learning and Sentence Retrieval from Electroencephalogram Recordings—0
Explain EEG-based End-to-end Deep Learning Models in the Frequency Domain—0
Beware of Overestimated Decoding Performance Arising from Temporal Autocorrelations in Electroencephalogram Signals—0
Combining Euclidean Alignment and Data Augmentation for BCI decoding—0
The Sandwich meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding—0
EEG decoding with conditional identification information—0
Geometric Neural Network based on Phase Space for BCI-EEG decodingCode0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network—0
Detecting gamma-band responses to the speech envelope for the ICASSP 2024 Auditory EEG Decoding Signal Processing Grand Challenge—0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding—0
Latent Alignment with Deep Set EEG Decoders—0
Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample VicinityCode1
Functional Graph Contrastive Learning of Hyperscanning EEG Reveals Emotional Contagion Evoked by Stereotype-Based Stressors—0
Large Transformers are Better EEG LearnersCode0
Distributionally Robust Cross Subject EEG Decoding—0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
Evaluating the structure of cognitive tasks with transfer learning—0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
Weight Freezing: A Regularization Approach for Fully Connected Layers with an Application in EEG ClassificationCode1
Time-space-frequency feature Fusion for 3-channel motor imagery classificationCode1
Relating EEG recordings to speech using envelope tracking and the speech-FFR—0
Deep Riemannian Networks for End-to-End EEG DecodingCode0
Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge DistillationCode1
Federated deep transfer learning for EEG decoding using multiple BCI tasks—0
Embedding neurophysiological signalsCode0
fMRI from EEG is only Deep Learning away: the use of interpretable DL to unravel EEG-fMRI relationshipsCode1
CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction—0
MAtt: A Manifold Attention Network for EEG DecodingCode1
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BEIRAPearson Correlation0.44—Unverified