ELEKTRONN: A highly configurable toolkit for training 3d/2d CNNs and general Neural Networks
Project Website: http://elektronn.org/
Github Link: https://github.com/ELEKTRONN/ELEKTRONN
ELEKTRONN is a deep learning toolkit that makes powerful neural networks accessible to scientists outside of the machine learning community.
ELEKTRONN is a highly configurable toolkit for training 3D/2D CNNs and general Neural Networks.
It is written in Python 2 and based on Theano, which allows CUDA-enabled GPUs to significantly accelerate the pipeline.
The package includes a sophisticated training pipeline designed for classification/localisation tasks on 3D/2D images. Additionally, the toolkit offers training routines for tasks on non-image data.
ELEKTRONN was created by Marius Killinger and Gregor Urban at the Max Planck Institute For Medical Research to solve connectomics tasks.