https://github.com/windowso/swim-asad
공식 코드SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory Spatial Attention Decoding
Papers with Code 아카이브
Electroencephalogram (EEG)
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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/wjq-learning/cbramod
공식 코드CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
https://github.com/woldier/EEGDiR
공식 코드https://github.com/wpf535236337/llms4ts
공식 코드A Survey of Spatio-Temporal EEG data Analysis: from Models to Applications
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/xalentis/stressschizophrenia
공식 코드https://github.com/xalentis/syntheticeeg
공식 코드https://github.com/xc-zhonghit/eeg-dg
공식 코드EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification
https://github.com/xiangzhang1015/adversarial_seizure_detection
공식 코드Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection
https://github.com/xiaobin-xs/EEG-competing-risks
공식 코드https://github.com/xiaozhangyes/cognitioncapturer
공식 코드CognitionCapturer: Decoding Visual Stimuli From Human EEG Signal With Multimodal Information
https://github.com/xinliangzhou/survey
공식 코드https://github.com/xjtu-eeg/libeer
공식 코드LibEER: A Comprehensive Benchmark and Algorithm Library for EEG-based Emotion Recognition
https://github.com/xmh1011/at-dgnn
공식 코드MEEG and AT-DGNN: Improving EEG Emotion Recognition with Music Introducing and Graph-based Learning
https://github.com/xqchen914/abat
공식 코드https://github.com/xuejiang16/ssl-torch
공식 코드Self-supervised Contrastive Learning for EEG-based Sleep Staging
https://github.com/xuxiran/asad_densenet
공식 코드A DenseNet-based method for decoding auditory spatial attention with EEG
https://github.com/xuyankun/stvig-for-reads-v
공식 코드VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViG
https://github.com/xuyankun/vsvig
공식 코드VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViG
https://github.com/yaricom/brainhash
공식 코드https://github.com/ycq091044/biot
공식 코드https://github.com/ycq091044/contrawr
공식 코드Self-supervised EEG Representation Learning for Automatic Sleep Staging
https://github.com/yeganehfrh/yare-gan
공식 코드https://github.com/yeon-lab/dream
공식 코드Domain Invariant Representation Learning and Sleep Dynamics Modeling for Automatic Sleep Staging
https://github.com/yeziyi1998/dl4eeg-classification
공식 코드Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System
https://github.com/yeziyi1998/uercm
공식 코드Towards a Better Understanding Human Reading Comprehension with Brain Signals
https://github.com/yi-ding-cs/LGG
공식 코드LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface
https://github.com/yi-ding-cs/TSception
공식 코드TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition
https://github.com/yi-ding-cs/eeg-deformer
공식 코드EEG-Deformer: A Dense Convolutional Transformer for Brain-computer Interfaces
https://github.com/yi-ding-cs/eeg-patchformer
공식 코드Decoding Human Attentive States from Spatial-temporal EEG Patches Using Transformers
https://github.com/yi-ding-cs/emt
공식 코드EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion Recognition
https://github.com/yi-ding-cs/masa-tcn
공식 코드https://github.com/yorgoon/diffe
공식 코드Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEG
https://github.com/yoshitatsumatsuda/orderingICA
공식 코드Efficient Estimation of Unique Components in Independent Component Analysis by Matrix Representation
https://github.com/youngeun1209/neurotalk
공식 코드Towards Voice Reconstruction from EEG during Imagined Speech
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.