SOTAVerified

Eeg Decoding

EEG Decoding - extracting useful information directly from EEG data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 74 papers

TitleStatusHype
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