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Brain Decoding
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Motor Brain Decoding is fundamental task for building motor brain computer interfaces (BCI).
Progress in predicting finger movements based on brain activity allows us to restore motor functions and improve rehabilitation process of patients.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pulp-platform/q-eegnet
공식 코드https://github.com/qinxinlan/eeg-experiment-to-understand-differences-in-blinking
공식 코드https://github.com/ravikiran-mane/FBCNet
공식 코드FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
https://github.com/reesekneeland/Second-Sight
공식 코드https://github.com/remilyoucef/sca-miner
공식 코드Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets
https://github.com/ricsinaruto/meg-group-decode
공식 코드https://github.com/rkobler/TSMNet
공식 코드SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
https://github.com/rxliang/vision
공식 코드https://github.com/sap-samples/salt
공식 코드https://github.com/sionan/miccai2024-restl
공식 코드https://github.com/siplab-gt/probabilistic-decomposed-linear-dynamical-systems
공식 코드Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics
https://github.com/slavaheroes/brain-captioning-with-gpt2
공식 코드Decoding fMRI Data into Captions using Prefix Language Modeling
https://github.com/smkia/interpretability
공식 코드Interpretability of Multivariate Brain Maps in Brain Decoding: Definition and Quantification
https://github.com/soinx0629/vis_dec_neurips
공식 코드Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
https://github.com/soupeeli/NeuroBOLT
공식 코드NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping
https://github.com/statistical-deep-learning/dcs-attention
공식 코드Differentiable Channel Selection in Self-Attention For Person Re-Identification
https://github.com/sylvchev/wcci-rgcon
공식 코드https://github.com/sylyoung/DeepTransferEEG
공식 코드T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs
https://github.com/t0nyliang/EEGMobile
공식 코드https://github.com/tfiedlerdev/wav2vec2forbrain
공식 코드https://github.com/thijor/pyntbci
공식 코드Exploring new territory: Calibration-free decoding for c-VEP BCI
https://github.com/thuir/brain-relevance-feedback
공식 코드https://github.com/tiehangd/ue-eeg
공식 코드Uncertainty Detection and Reduction in Neural Decoding of EEG Signals
https://github.com/timeflux/demos
공식 코드End-to-end P300 BCI using Bayesian accumulation of Riemannian probabilities
https://github.com/tonahdztoro/Toward_asynchronous
공식 코드Toward asynchronous EEG-based BCI: Detecting imagined words segments in continuous EEG signals
https://github.com/tonahdztoro/onset_detection
공식 코드An algorithm for onset detection of linguistic segments in continuous electroencephalogram signals
https://github.com/transconnectome/mbbn
공식 코드https://github.com/vlawhern/arl-eegmodels
공식 코드EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
https://github.com/weihaox/UMBRAE
공식 코드https://github.com/wenhui0206/neurogpt
공식 코드https://github.com/why135724/SWPC
공식 코드Motor Imagery Classification for Asynchronous EEG-Based Brain-Computer Interfaces
https://github.com/williamro/eeg-denoise
공식 코드DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature Reuse
https://github.com/wzwvv/DBConformer
공식 코드DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
https://github.com/wzwvv/MCNet
공식 코드MVCNet: Multi-View Contrastive Network for Motor Imagery Classification
https://github.com/xc-zhonghit/eeg-dg
공식 코드EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.