Papers with Code 아카이브

EEG

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/prajwalsingh/eegstylegan-ada

공식 코드

Learning Robust Deep Visual Representations from EEG Brain Recordings

https://github.com/promise-z5q2sq/eeg-imagenet-dataset

공식 코드

EEG-ImageNet: An Electroencephalogram Dataset and Benchmarks with Image Visual Stimuli of Multi-Granularity Labels

https://github.com/ptirupat/ThoughtViz

공식 코드

Correct block-design experiments mitigate temporal correlation bias in EEG classification

https://github.com/pulp-bio/bmi-odcl

공식 코드

Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces

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

공식 코드

Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine Interfaces

https://github.com/pythonot/convolutional-monge-mapping-normalization

공식 코드

Convolutional Monge Mapping Normalization for learning on sleep data

https://github.com/qinxinlan/eeg-experiment-to-understand-differences-in-blinking

공식 코드

Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms

https://github.com/qiuyuezhibo/xaieeg

공식 코드

Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG Signals

https://github.com/ravikiran-mane/FBCNet

공식 코드

FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface

https://github.com/ravikiranrao/pd-eeg

공식 코드

Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG Signals

https://github.com/ricsinaruto/meg-transfer-decoding

공식 코드

Foundational GPT Model for MEG

https://github.com/rkobler/TSMNet

공식 코드

SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG

https://github.com/rkobler/interpret_lin_rts_mdls

공식 코드

On the interpretation of linear Riemannian tangent space model parameters in M/EEG

https://github.com/robintibor/auto-eeg-diagnosis-example

공식 코드

Deep learning with convolutional neural networks for decoding and visualization of EEG pathology

https://github.com/rosedwayane/aieeg

공식 코드

IC-U-Net: A U-Net-based Denoising Autoencoder Using Mixtures of Independent Components for Automatic EEG Artifact Removal

https://github.com/rsbci/conceft-spindle

공식 코드

Unveil Sleep Spindles with Concentration of Frequency and Time

https://github.com/ruiqirichard/eegeyenet-vit

공식 코드

ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data

https://github.com/runkzhang/epint

공식 코드

Cross-Modal Epileptic Signal Harmonization: Frequency Domain Mapping Quantization for Pre-training a Unified Neurophysiological Transformer

https://github.com/ryersonmultimedialab/emotionrecognitionuda

공식 코드

Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain Adaptation

https://github.com/salim-lysiun/arnn

공식 코드

ARNN: Attentive Recurrent Neural Network for Multi-channel EEG Signals to Identify Epileptic Seizures

https://github.com/samuelhorvath/granger-causality-with-nn

공식 코드

Granger Causality using Neural Networks

https://github.com/samuelracz/MMSPM

공식 코드

Multi-Modal Spectral Parametrization Method (MMSPM) for analyzing EEG activity with distinct scaling regimes

https://github.com/sccn/deep-channel-harmonization

공식 코드

Deep learning applied to EEG data with different montages using spatial attention

https://github.com/sccn/testica

공식 코드

A Framework to Evaluate Independent Component Analysis applied to EEG signal: testing on the Picard algorithm

https://github.com/serg99io/dstf-sleepstaging

공식 코드

A novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classification

https://github.com/sgoerttler/msa-cnn

공식 코드

Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification

https://github.com/shalit-lab/deep-scientific-discovery

공식 코드

Using Deep Networks for Scientific Discovery in Physiological Signals

https://github.com/sharajpanwar/CC-WGAN-GP

공식 코드

Modeling EEG data distribution with a Wasserstein Generative Adversarial Network to predict RSVP Events

https://github.com/sionan/miccai2024-restl

공식 코드

Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification

https://github.com/sislam99/fmri_state_transition_dynamics

공식 코드

State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysis

https://github.com/sonycslparis/audioic

공식 코드

Estimating Musical Surprisal in Audio

https://github.com/soupeeli/NeuroBOLT

공식 코드

NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping

https://github.com/spiresearch/sacd

공식 코드

Seeing your sleep stage: cross-modal distillation from EEG to infrared video

https://github.com/spm/spm

공식 코드

BSD: a Bayesian framework for parametric models of neural spectra

https://github.com/sremes/wishart-gibbs-kernel

공식 코드

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

https://github.com/svaneynd/structured-cmtf

공식 코드

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data

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