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EEG

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/modeeric/eegvit-tcnet

EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction

https://github.com/navsnav/Minimal-RBD-Detection

Screening for REM Sleep Behaviour Disorder with Minimal Sensors

https://github.com/ncclab-sustech/eeg_image_decode

Decoding Natural Images from EEG for Object Recognition

https://github.com/nicolasigor/cmorlet-tensorflow

RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection

https://github.com/norahollenstein/reading-task-classification

Reading Task Classification Using EEG and Eye-Tracking Data

https://github.com/okbalefthanded/ssvepformer

A Transformer-based deep neural network model for SSVEP classification

https://github.com/pelednoam/mmvt

Multi-Modal Neuroimaging Analysis and Visualization Tool (MMVT)

https://github.com/perslev/U-Time

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

https://github.com/pieeg-club/PiEEG_Kit

PiEEG kit - bioscience Lab in home for your Brain and Body

https://github.com/pulp-platform/hwpe-tb

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

https://github.com/pulp-platform/pulp

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

https://github.com/pulp-platform/pulpissimo

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

https://github.com/pwc-1/Paper-9/tree/main/3/SGDR

SGDR: Stochastic Gradient Descent with Warm Restarts

https://github.com/pwc-1/Paper-9/tree/main/7/RGNN

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

https://github.com/rczhen/Movement-Classification-based-on-Electroencephalography-EEG-Signals

Deep learning with convolutional neural networks for EEG decoding and visualization

https://github.com/rwightman/pytorch-image-models

SGDR: Stochastic Gradient Descent with Warm Restarts

https://github.com/samiatto/colide

Generalized Concomitant Multi-Task Lasso for sparse multimodal regression

https://github.com/sari-saba-sadiya/EEG-Channel-Interpolation-Using-Deep-Encoder-decoder-Networks

EEG Channel Interpolation Using Deep Encoder-decoder Netwoks

https://github.com/satyam9753/NNFL-EEG-DRCNN

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

https://github.com/sergiojx/ML_DSP

Cerebral Signal Instantaneous Parameters Estimation MATLAB Toolbox - User Guide Version 2.3

https://github.com/sfvnielsen/ndfc

Nonparametric Modeling of Dynamic Functional Connectivity in fMRI Data

https://github.com/sweichwald/coroICA-R

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

https://github.com/sweichwald/coroICA-matlab

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

https://github.com/teptwomey/deep_learning_architectures_for_fscv

Transformer-based Spatial-Temporal Feature Learning for EEG Decoding

https://github.com/tiehangd/MUPS-EEG

Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification

https://github.com/tmbluth/Distracted-Drivers-Detection

SGDR: Stochastic Gradient Descent with Warm Restarts

https://github.com/tom-beer/deep-scientific-discovery

Using Deep Networks for Scientific Discovery in Physiological Signals

https://github.com/tracy6955/IBM_seizure_data

SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

https://github.com/uzkent/EfficientObjectDetection

HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

https://github.com/veikkahonkanen/Seizurenet-replica

SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

https://github.com/vinuni-vishc/transformer-gait-analysis

SGDR: Stochastic Gradient Descent with Warm Restarts

https://github.com/wangjinzhuo/wearables

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

https://github.com/xiangzhang1015/Brain_typing

Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals

https://github.com/xiangzhang1015/EEG_Shape_Reconstruction

Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals

https://github.com/xy1802/EEGLearn_mytest

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

https://github.com/yufat48/pulpissimo

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.