Neugen
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Emojiintelligence | 1,328 | 5 years ago | mit | Swift | ||||||
| Neural Network built in Apple Playground using Swift | ||||||||||
| Bindsnet | 1,214 | 7 days ago | 14 | agpl-3.0 | Python | |||||
| Simulation of spiking neural networks (SNNs) using PyTorch. | ||||||||||
| Genann | 1,124 | 2 years ago | 6 | zlib | C | |||||
| simple neural network library in ANSI C | ||||||||||
| Ocr | 1,120 | 7 years ago | other | JavaScript | ||||||
| Neural network OCR. | ||||||||||
| Neataptic | 978 |  | 24 | 5 | 4 years ago | 81 | October 21, 2017 | 76 | other | JavaScript |
| :rocket: Blazing fast neuro-evolution & backpropagation for the browser and Node.js | ||||||||||
| Digit Classifier | 780 | 3 years ago | mit | Python | ||||||
| A single handwritten digit classifier, using the MNIST dataset. Pure Numpy. | ||||||||||
| Spikingjelly | 636 | 5 days ago | 41 | August 22, 2020 | 56 | other | Python | |||
| SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch. | ||||||||||
| Deep Learning Illustrated | 543 | a month ago | 6 | mit | Jupyter Notebook | |||||
| Deep Learning Illustrated (2020) | ||||||||||
| Synthesizing | 470 | 3 years ago | 2 | mit | Python | |||||
| Code for paper "Synthesizing the preferred inputs for neurons in neural networks via deep generator networks" | ||||||||||
| Spiking Neural Network | 434 | 4 years ago | 7 | apache-2.0 | Python | |||||
| Pure python implementation of SNN | ||||||||||
NeuGen
NeuGen is made for generation of dendritic and axonal morphology of realistic neurons and networks in 3D
NeuGen generates nonidentical neurons of morphological classes of the cortex, e.g., pyramidal cells and stellate neurons, and synaptically connected neural networks in 3D. It is based on sets of descriptive and iterative rules which represent the axonal and dendritic geometry of neurons by inter-correlating morphological parameters. The generation algorithm stochastically samples parameter values from distribution functions induced by experimental data. The generator is adequate for the geometric modelling and for the construction of the morphology.
The generated neurons can be exported into a 3D graphic format for visualization and into multi-compartment files for simulations with the program NEURON. NeuGen is intended for scientists aiming at simulations of realistic networks in 3D.
Build prerequisites
- Ant >= 1.9
- JDK >= 6 and JDK <= 12
Howto build NeuGen
- Netbeans: Clean & Build
- Ant: ant release from NeuGen folder
Howto run NeuGen
- Netbeans: Run File
NeuGenApp.java - Terminal: Go to rls folder - execute run script according to your OS
Releases
NeuGen 2.0 - git tag v2.0 Current development on devel branch, current stable on master branch. See also the project website NeuGen and NeuroBox3D.
Samples
