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Eeg Decoding

EEG Decoding - extracting useful information directly from EEG data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–74 of 74 papers

TitleStatusHype
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
Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model—0
Deep Correlation Analysis for Audio-EEG Decoding—0
Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface—0
Detecting gamma-band responses to the speech envelope for the ICASSP 2024 Auditory EEG Decoding Signal Processing Grand Challenge—0
Distributionally Robust Cross Subject EEG Decoding—0
Dual-TSST: A Dual-Branch Temporal-Spectral-Spatial Transformer Model for EEG Decoding—0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BEIRAPearson Correlation0.44—Unverified