https://github.com/dungscout96/DL-EEG
공식 코드Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral Features
Papers with Code 아카이브
Electroencephalogram (EEG)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Electroencephalogram (EEG) is a method of recording brain activity using electrophysiological indexes. When the brain is active, a large number of postsynaptic potentials generated synchronously by neurons are formed after summation. It records the changes of electric waves during brain activity and is the overall reflection of the electrophysiological activities of brain nerve cells on the surface of cerebral cortex or scalp. Brain waves originate from the postsynaptic potential of the apical dendrites of pyramidal cells. The formation of synchronous rhythm of EEG is also related to the activity of nonspecific projection system of cortex and thalamus. EEG is the basic theoretical research of brain science. EEG monitoring is widely used in its clinical application.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dykuang/bci-attention
공식 코드A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data
https://github.com/eeg-augmentation-benchmark/eeg-augmentation-benchmark-2022
공식 코드Data augmentation for learning predictive models on EEG: a systematic comparison
https://github.com/eeyhsong/nice-eeg
공식 코드https://github.com/elouayas/eegsimpleconv
공식 코드A Strong and Simple Deep Learning Baseline for BCI MI Decoding
https://github.com/emadeldeen24/ADAST
공식 코드ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training
https://github.com/emadeldeen24/eval_ssl_ssc
공식 코드Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation
https://github.com/emmanuelkalunga/Online-SSVEP
공식 코드Using Riemannian geometry for SSVEP-based Brain Computer Interface
https://github.com/emotionlab/eegain
공식 코드Evaluation in EEG Emotion Recognition: State-of-the-Art Review and Unified Framework
https://github.com/enozari/rest-system-id
공식 코드Is the brain macroscopically linear? A system identification of resting state dynamics
https://github.com/esl-epfl/epilepsy2bids
공식 코드https://github.com/esl-epfl/epilepsy_performance_metrics
공식 코드https://github.com/esl-epfl/sz-validation-framework
공식 코드https://github.com/eunjin93/SICR_BCI
공식 코드Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI
https://github.com/facebookresearch/brainmagick
공식 코드Decoding speech perception from non-invasive brain recordings
https://github.com/fanajman/the-brain-uses-renewal-points-to-model-random-sequences-of-stimuli
공식 코드The brain uses renewal points to model random sequences of stimuli
https://github.com/fardinghorbani/EEGsig
공식 코드EEGsig: an open-source machine learning-based toolbox for EEG signal processing
https://github.com/fchest/darnet
공식 코드https://github.com/fchest/m3anet
공식 코드M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
https://github.com/fpgdubost/CIFAR-10-Sparsely-Labeled-Sequential-Data
공식 코드https://github.com/gabrielrpalma/understandinglearningwithml
공식 코드https://github.com/galvinlim/agtcnet
공식 코드AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG Classification
https://github.com/gasiki/eeg-reptile
공식 코드EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs
https://github.com/gaurav71531/UUknowns
공식 코드https://github.com/gemeinl/auto-eeg-diagnosis-comparison
공식 코드https://github.com/gemeinl/eeg-brain-age
공식 코드https://github.com/geometricbci/deep-optimal-transport-for-domain-adaptation-on-spd-manifolds
공식 코드Deep Optimal Transport for Domain Adaptation on SPD Manifolds
https://github.com/gianpaolopalo13/in_ear_eeg_vs_psg
공식 코드https://github.com/gibranfp/P300-CNNT
공식 코드A few filters are enough: Convolutional Neural Network for P300 Detection
https://github.com/gist-ailab/IITNet-official
공식 코드https://github.com/gist-ailab/sleepyco
공식 코드SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning
https://github.com/gitzh-chen/liebn
공식 코드https://github.com/gitzh-chen/spdmlr
공식 코드Riemannian Multinomial Logistics Regression for SPD Neural Networks
https://github.com/gon-uri/detach_rocket
공식 코드https://github.com/guangyaodou/eeg4students
공식 코드EEG4Students: An Experimental Design for EEG Data Collection and Machine Learning Analysis
https://github.com/guangyaodou/time_majority_voting
공식 코드Time Majority Voting, a PC-based EEG Classifier for Non-expert Users
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.