leanringgit's Stars
3b1b/manim
Animation engine for explanatory math videos
binary-husky/gpt_academic
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
WZMIAOMIAO/deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
dair-ai/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
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
SuperBruceJia/EEG-DL
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
braindecode/braindecode
Deep learning software to decode EEG, ECG or MEG signals
eeyhsong/EEG-Conformer
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
DeepBCI/Deep-BCI
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
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.
zwcolin/EEG-Transformer
A ViT based transformer applied on multi-channel time-series EEG data for motor imagery classification
breuderink/eegtools
Collection of Python modules for EEG analysis. Includes EDF+ and BDF loaders, scalp plots and commonly used spatial filters.
yi-ding-cs/TSception
[TAFFC-2022] PyTorch implementation of TSception v2
ethorsrud/Master
sharajpanwar/CC-WGAN-GP
Repo: IEEE TNSRE Article "Modeling EEG data distribution with a Wasserstein Generative Adversarial Network (WGAN) to predict RSVP Events" - Keras implementation
cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI
In this project, we implemented 7 interpretation techniques on two benchmark deep learning models "EEGNet" and "InterpretableCNN" for EEG-based BCI. The methods include: gradient×input, DeepLIFT, integrated gradient, layer-wise relevance propagation (LRP), saliency map, deconvolution, and guided backpropagation
jesus-333/Dynamic-PyTorch-Net
Class to automatic create Convolutional Neural Network in PyTorch
Tammie-Li/RSVP-EEGNet
PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interface
bowenliee/XGB-DIM-for-RSVP
An ensemble learning method for EEG classification in RSVP tasks
hsuan9027/MI-STViT
Motor Imagery EEG Classification Model based on Visual Transformer with Spatiotemporal Information Extraction
yuvfried/eegtools
Tools for analysis of EEG and ERP signals. Inculdes data_ingestion tool for MATLAB structure, analysis of components and plotting tools
EugenioBertolini/eegCNN-AMUSE
CNN for ERP classification of the AMUSE dataset.
oscar-anderson/EEG-Fringe-P3-analysis
For my MSc dissertation, and in my role as a research data analyst, I am undertaking an analysis of electroencephalography data to investigate whether detection of the P300 neural signal can be utilised within an EEG Brain-Computer Interface to discern information from the minds of individuals, without the need for explicit communication.