Deemo921's Stars
zyglovepp/code-gpt
通过将整个项目的代码转成一个txt格式文件，通过langchain和chatgpt帮助我们更好的理解代码。
ChristopherSims/FMRI_ADHD_Classification
3D_CNN classification of ADHD from FMRI data
ai-dawang/PlugNPlay-Modules
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
largeapp/M2DCNN
ustc-bmec/fMRI-Conv-Att
harsharaman/bold5000_fmri
Implementation of LSTM and CNN models for classification of visual stimuli from fMRI data on BOLD5000 dataset
AmbomBee/tfMRI_CNN
Code for the Masterthesis "A Deep Vision Approach for Feature Extraction of 4D task-based fMRI Sequences"
KnightofDawn/BrainBench-CNNVisualizations
We study the correlation between the CNN activations of various images from ImageNet on CNN architecture such as ResNet50, VGGNet, Inception V3, AlexNet and with that of the Brain data vectors obtained through FMRI, EEG, MEG etc
tehilaeitan/MRI-fMRI-Alzheimer-Prediction-DL
Deep learning models for predicting Alzheimer's Disease stages using MRI and fMRI data. It includes variety of Models like 3D-CNN, 2D-CNN, and Vision Transformer, achieving up to 95.6% accuracy in distinguishing Alzheimer's, MCI, and Healthy Controls for early diagnosis.
linqiuhua/fMRI_SSPNet-An-interpretable-3D-CNN-for-classifying-schizophrenia
"SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data," published in Medical Image Analysis
deontaepharr/Diagnosing-ADHD-With-ConvLSTM
Classifying ADHD fMRI data with a CNN+LSTM Model
huawei-lin/HCP_Dataset_Download_Automatically_Script
This script can download the HCP dataset automatically from amazon s3 browser by using python. You can download tfMRI, rfMRI, dfMRI, MEG etc. dataset from amazon s3 of HCP.
Serpeve/EEGSym
Open implementation and code from the publication "EEGSym: Overcoming Intersubject Variability in Motor Imagery Based BCIs with Deep Learning"
OrangeP0P/EDAN
Baizhige/EEGResearchHub
A trusted repository for groundbreaking EEG research code. Some peer-reviewed algorithms (such as EEG data augmentation techniques, EEG classification models) to push the boundaries of neuroscience.
eeyhsong/EEG-Transformer
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.
Altaheri/EEG-ATCNet
Attention temporal convolutional network for EEG-based motor imagery classification
mikespook/Learning-Go-zh-cn
一本学习 Go 语言的免费电子书。
gopl-zh/gopl-zh.github.com
:books: Go语言圣经中文版 🇨🇳
vlawhern/arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
martinwimpff/channel-attention
braindecode/braindecode
Deep learning software to decode EEG, ECG or MEG signals
EdgarMoyete/Deep-Learning-BCI-IV-2a
Clasificacion de imagenes motoras en señales EEG con CNN, LSTM y otros clasificadores
dalinzhangzdl/BCI_MI_Wavelet_CNN
Using wavelet transform to extract time-frequency features of motor imagery EEG signals, and classify it by convolutional neural network
KindXiaoming/pykan
Kolmogorov Arnold Networks
robintibor/high-gamma-dataset
ManTouCIBR/CNN-training-testing-templates-for-processing-EEG-signals
A template: for deep learning processing BCI-2A-Data, including loading data, preprocessing, training, testing, saving the best model, visualization of results (loss, acc, obfuscation, PR, RE)
vkola-lab/azrt2020
Enhancing magnetic resonance imaging driven Alzheimer’s disease classification performance using generative adversarial learning
giaminhgist/3D-DAM
A reproducible 3D convolutional neural network with dual attention module (3D-DAM) for Alzheimer's disease classification