https://github.com/anders-s-olsen/coupled-generator-decomposition
공식 코드Coupled generator decomposition for fusion of electro- and magnetoencephalography data
Papers with Code 아카이브
Electroencephalogram (EEG)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 3
- 보존된 평가 기록
- 5
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/andersgmadsen/speed
공식 코드SPEED: Scalable Preprocessing of EEG Data for Self-Supervised Learning
https://github.com/andersgmadsen/tcav-bendr
공식 코드https://github.com/andersxa/cslp-ae
공식 코드https://github.com/anp-scp/fast_bci
공식 코드Evaluating Fast Adaptability of Neural Networks for Brain-Computer Interface
https://github.com/anranknight/EEG-Transformer
공식 코드Transformer-based Spatial-Temporal Feature Learning for EEG Decoding
https://github.com/ardkastrati/eegeyenet
공식 코드https://github.com/aristotelisballas/biodg
공식 코드Towards Domain Generalization for ECG and EEG Classification: Algorithms and Benchmarks
https://github.com/ayahia1/kdd-ml
공식 코드https://github.com/ayushayt/imaginedspeechrecognition
공식 코드Analysis of EEG frequency bands for Envisioned Speech Recognition
https://github.com/baizhige/eegunity
공식 코드EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model
https://github.com/bangyaozhao/glass
공식 코드https://github.com/bbaaii/DreamDiffusion
공식 코드DreamDiffusion: Generating High-Quality Images from Brain EEG Signals
https://github.com/berndporr/deepNeuronalFilter
공식 코드https://github.com/bidalab/improve
공식 코드https://github.com/bidalab/mebal2
공식 코드mEBAL2 Database and Benchmark: Image-based Multispectral Eyeblink Detection
https://github.com/bingzant/beats
공식 코드BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool System
https://github.com/biomedical-data-analysis-laboratory/multicentric-ml-parkinson-detection
공식 코드https://github.com/biomedical-signal-processing/sleepyland
공식 코드SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models
https://github.com/bobwangpku/eeg-stimulus-match-mismatch
공식 코드https://github.com/bohu615/corticomuscular-eigen-encoder
공식 코드Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios
https://github.com/bomatter/participant-diversity-paper
공식 코드Is Limited Participant Diversity Impeding EEG-based Machine Learning?
https://github.com/boxinz17/FuDGE
공식 코드Direct Estimation of Differential Functional Graphical Models
https://github.com/braindecode/braindecode
공식 코드Deep learning with convolutional neural networks for EEG decoding and visualization
https://github.com/brianxiang123/eegetcovariatedistributionalshift
공식 코드https://github.com/bryantdom/driver-drowsiness-monitoring
공식 코드LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring
https://github.com/bsalafia/cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical
공식 코드https://github.com/buptanteeg/beats
공식 코드BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool System
https://github.com/buttersen/libeer
공식 코드LibEER: A Comprehensive Benchmark and Algorithm Library for EEG-based Emotion Recognition
https://github.com/caglarcakan/sleeping_brain
공식 코드https://github.com/calakus/RFCCA
공식 코드Conditional canonical correlation estimation based on covariates with random forests
https://github.com/carlosloza/DNDBN
공식 코드Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling
https://github.com/carraraig/Phase-SPDNet
공식 코드Geometric Neural Network based on Phase Space for BCI-EEG decoding
https://github.com/carraraig/augmented_covariance_bci
공식 코드Classification of BCI-EEG based on augmented covariance matrix
https://github.com/cecnl/eeg-kd
공식 코드https://github.com/cecnl/matt
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.