https://github.com/philipph77/acse-framework
공식 코드Exploiting Multiple EEG Data Domains with Adversarial Learning
Papers with Code 아카이브
Electroencephalogram (EEG)
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- 평가표
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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/pidahbus/DCoM
공식 코드https://github.com/pieeg-club/PiEEG-16
공식 코드https://github.com/pierreHmbt/Tensor_CDL
공식 코드Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis
https://github.com/pingala-institute/Bayes-medicaldataimputation
공식 코드Bayes-CATSI: A variational Bayesian deep learning framework for medical time series data imputation
https://github.com/pingayush/INTELLIGUARD-Enhancing-Network-Security
공식 코드https://github.com/plcrodrigues/hnpe
공식 코드HNPE: Leveraging Global Parameters for Neural Posterior Estimation
https://github.com/pquochuy/l-seqsleepnet
공식 코드L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging
https://github.com/prajwalsingh/eegstylegan-ada
공식 코드Learning Robust Deep Visual Representations from EEG Brain Recordings
https://github.com/promise-z5q2sq/eeg-imagenet-dataset
공식 코드https://github.com/ptirupat/ThoughtViz
공식 코드Correct block-design experiments mitigate temporal correlation bias in EEG classification
https://github.com/pulp-bio/bmi-odcl
공식 코드https://github.com/pulp-platform/q-eegnet
공식 코드https://github.com/pythonot/convolutional-monge-mapping-normalization
공식 코드Convolutional Monge Mapping Normalization for learning on sleep data
https://github.com/qinxinlan/eeg-experiment-to-understand-differences-in-blinking
공식 코드https://github.com/qiuyuezhibo/xaieeg
공식 코드Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG Signals
https://github.com/ravikiran-mane/FBCNet
공식 코드FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
https://github.com/ravikiranrao/pd-eeg
공식 코드Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG Signals
https://github.com/ricsinaruto/meg-transfer-decoding
공식 코드https://github.com/rkobler/TSMNet
공식 코드SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
https://github.com/rkobler/interpret_lin_rts_mdls
공식 코드On the interpretation of linear Riemannian tangent space model parameters in M/EEG
https://github.com/robintibor/auto-eeg-diagnosis-example
공식 코드Deep learning with convolutional neural networks for decoding and visualization of EEG pathology
https://github.com/rosedwayane/aieeg
공식 코드https://github.com/rsbci/conceft-spindle
공식 코드Unveil Sleep Spindles with Concentration of Frequency and Time
https://github.com/ruiqirichard/eegeyenet-vit
공식 코드ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data
https://github.com/runkzhang/epint
공식 코드https://github.com/ryersonmultimedialab/emotionrecognitionuda
공식 코드https://github.com/salim-lysiun/arnn
공식 코드https://github.com/samuelhorvath/granger-causality-with-nn
공식 코드https://github.com/samuelracz/MMSPM
공식 코드https://github.com/sccn/deep-channel-harmonization
공식 코드Deep learning applied to EEG data with different montages using spatial attention
https://github.com/sccn/testica
공식 코드https://github.com/serg99io/dstf-sleepstaging
공식 코드https://github.com/sgoerttler/msa-cnn
공식 코드Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification
https://github.com/shalit-lab/deep-scientific-discovery
공식 코드Using Deep Networks for Scientific Discovery in Physiological Signals
https://github.com/sharajpanwar/CC-WGAN-GP
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.