https://github.com/justlfc03/mstnet
공식 코드Toward Robust Early Detection of Alzheimer's Disease via an Integrated Multimodal Learning Approach
Papers with Code 아카이브
Electroencephalogram (EEG)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/jzhangu/basen
공식 코드https://github.com/jzk00/eeg-dif
공식 코드https://github.com/kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition
공식 코드Self-supervised Group Meiosis Contrastive Learning for EEG-Based Emotion Recognition
https://github.com/kazabana/eegmatch
공식 코드https://github.com/keruiwu/SeizureTransformer
공식 코드https://github.com/kesslerr/m4d
공식 코드https://github.com/kgr20/e2fnet
공식 코드From Brainwaves to Brain Scans: A Robust Neural Network for EEG-to-fMRI Synthesis
https://github.com/khaledsaab/eeg_robustness
공식 코드Towards trustworthy seizure onset detection using workflow notes
https://github.com/killingbear999/eeg-emg-lstm
공식 코드Upper Limb Movement Recognition utilising EEG and EMG Signals for Rehabilitative Robotics
https://github.com/kkipngenokoech/Hybrid-EEGNET-CharRNN-predictor
공식 코드Improving SSVEP BCI Spellers With Data Augmentation and Language Models
https://github.com/klean2050/eeg_crossmodal
공식 코드https://github.com/kolcs/GoPar
공식 코드https://github.com/kolcs/bionic_apps
공식 코드https://github.com/komdec/detectsleepnet
공식 코드An Interpretable and Efficient Sleep Staging Algorithm: DetectsleepNet
https://github.com/kovalalvi/beira
공식 코드https://github.com/kssyyy/cmcrd
공식 코드CMCRD: Cross-Modal Contrastive Representation Distillation for Emotion Recognition
https://github.com/lbinmeng/adversarial_filter
공식 코드Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces
https://github.com/lee-jhwn/fesde
공식 코드Toward Fully-End-to-End Listened Speech Decoding from EEG Signals
https://github.com/lee-jhwn/icassp25-fesde-phoneme
공식 코드Enhancing Listened Speech Decoding from EEG via Parallel Phoneme Sequence Prediction
https://github.com/liangyubuaa/milmer
공식 코드Milmer: a Framework for Multiple Instance Learning based Multimodal Emotion Recognition
https://github.com/liaoeuan/sincalignnet
공식 코드https://github.com/likith012/muleeg
공식 코드https://github.com/lina-usc/jansen-rit-model-benchmarking-deep-learning
공식 코드Deep Jansen-Rit Parameter Inference for Model-Driven Analysis of Brain Activity
https://github.com/lixujin99/tsformer-sa
공식 코드A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI Decoding
https://github.com/lizixing23/AMBOKD
공식 코드https://github.com/loshchil/SGDR
공식 코드https://github.com/lu-wo/detrtime
공식 코드https://github.com/lucapton/ICLabel-Train
공식 코드ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
https://github.com/luigisigillo/gwit
공식 코드Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion Models
https://github.com/luke-marks0/mutual-feature-regularization
공식 코드Enhancing Neural Network Interpretability with Feature-Aligned Sparse Autoencoders
https://github.com/mHealthBuet/ASSC
공식 코드End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
https://github.com/mac0504/mmme
공식 코드MMME: A Spontaneous Multi-Modal Micro-Expression Dataset Enabling Visual-Physiological Fusion
https://github.com/martinwimpff/channel-attention
공식 코드EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanisms
https://github.com/martinwimpff/eeg-continual
공식 코드https://github.com/martinwimpff/eeg-otta
공식 코드Calibration-free online test-time adaptation for electroencephalography motor imagery decoding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.