Brain Open Source Projects

Swift Featured Projects in brain Mapping

🤖 GPU accelerated Neural networks in JavaScript for Browsers and Node.js

Train a Neural Network to play Snake using a Genetic Algorithm

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

A curated list of awesome Public Zettelkastens 🗄️ / Second Brains 🧠 / Digital Gardens 🌱

Org-mode wiki + concept-mapping

NeuroLab Android https://github.com/fossasia/neurolab-android/raw/apk/neurolab-dev-debug.apk

A curated list of awesome neuroscience libraries, software and any content related to the domain.

SOTA medical image segmentation methods based on various challenges

Neurolab Hardware

Curated Collection of BCI resources

Firmware for Neurolab Hardware

MICCAI 2019-2023 Open Source Papers

🧠🗼

Arduino library for reading Neurosky EEG brainwave data. (Tested with the MindFlex and Force Trainer toys.)

The MATLAB toolbox for MEG, EEG and iEEG analysis

My personal knowledge repository

CrackQ: A Python Hashcat cracking queue system

A Python library for creating and simulating large-scale brain models

The iPhone version of News/YC, a Hacker News reader and interactive iOS application.

The X Toolkit

🚀 100+ mini-projects demonstrating the power of concise code. Perfect for learning, portfolio building, and first-time open source contributors. Under 100 lines each!

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI

fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.

A light theme for Visual Studio Code

A publicly-editable collection of open computational neuroscience resources

A tool to graphically visualize SIMD code

A Implementation of SpecAugment with Tensorflow & Pytorch, introduced by Google Brain

Neurokernel Project

TopDown Engine extensions created by the community

U-Net Brain Tumor Segmentation

Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿‍🔬

How to 3D print your brain from a T1 MRI image.

Tensorflow implementation of pixel-recursive-super-resolution(Google Brain paper: https://arxiv.org/abs/1702.00783)

AI residency programs information

Ruby + Bot = Ruboty

Implementing Stand-Alone Self-Attention in Vision Models using Pytorch

Self-improving decision organism

This is Math-Puzzle game made in flutter and available on Playstore & AppStore,Math Matrix is a Math Game that tries to improvise your math skills in a fun way.

MRI brain extraction tool

An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

知乎答题王(头脑王者)辅助工具

Converting real-time EEG into sounds, music and visual effects

code for reading and processing Allen Institute for Brain Science data

[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

Neural networks toolbox focused on medical image analysis

Brain Imaging Analysis Kit

Brain Imaging Data Structure (BIDS) Specification

Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats

Python 3.x based AIML 2.0 Chatbot interpreter, framework, related programs and knowledge files

Natural language virtual assistant using Node.js + Bootstrap

brain connectivity toolbox for python

A Gatsby theme to build Andy style websites. 📑

Mocking utility for PHP functions and WordPress plugin API

Brain Modeling Toolkit

Brain tumor segmentation for MICCAI 2017 BraTS challenge

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.