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Eeg Decoding
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EEG Decoding - extracting useful information directly from EEG data.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Improved Motor Imagery Classification Using Adaptive Spatial Filters Based on Particle Swarm Optimization Algorithm
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification
Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample Vicinity
Functional Graph Contrastive Learning of Hyperscanning EEG Reveals Emotional Contagion Evoked by Stereotype-Based Stressors
Large Transformers are Better EEG Learners
Distributionally Robust Cross Subject EEG Decoding
Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning
Evaluating the structure of cognitive tasks with transfer learning
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks
Weight Freezing: A Regularization Approach for Fully Connected Layers with an Application in EEG Classification
Time-space-frequency feature Fusion for 3-channel motor imagery classification
Relating EEG recordings to speech using envelope tracking and the speech-FFR
Deep comparisons of Neural Networks from the EEGNet family
Deep Riemannian Networks for End-to-End EEG Decoding
Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge Distillation
Federated deep transfer learning for EEG decoding using multiple BCI tasks
Embedding neurophysiological signals
fMRI from EEG is only Deep Learning away: the use of interpretable DL to unravel EEG-fMRI relationships
CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction
A Transformer-based deep neural network model for SSVEP classification
MAtt: A Manifold Attention Network for EEG Decoding
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding
Physics-inform attention temporal convolutional network for EEG-based motor imagery classification
A Hybrid Complex-valued Neural Network Framework with Applications to Electroencephalogram (EEG)
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection
SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification
Analyzing EEG Data with Machine and Deep Learning: A Benchmark
A Decomposition-Based Hybrid Ensemble CNN Framework for Driver Fatigue Recognition
An Olfactory EEG Signal Classification Network Based on Frequency Band Feature Extraction
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition
ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model Interpretation
Uncertainty Detection and Reduction in Neural Decoding of EEG Signals
Toward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey
EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
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