An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures
A web-based interactive tool for training deep neural networks for segmentation tasks. It consists of a server backend that runs on a high-performance GPU compute node, and a front end user interface that runs on a web browser. User configures a classifier, the classes of objects to be detected, and the set of images to use for training and validation.
Efficient Compression of Segmentation Data For Connectomics
Compresso is a new compression scheme for label data that outperforms existing approaches by using a sliding window to exploit redundancy across border regions in 2D and 3D.
Source code: https://github.com/VCG/compresso