Graphene U-Net v1
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Graphene U-Net is a library that provides a simplified platform for training deep neural networks for the task of microscopy image segmentation. It contains functions and classes that make the process of training a neural network simple such that non-ML experts can train and evaluate models on their own datasets. It uses Pytorch as a backend and can run on both CUDA-enable GPUs and CPUs. It contains the main library file Microscopy_Unet.py as well as unet.py which contains the UNET model used for this software. This can be replaced with any other fully convolutional deep learning architecture with relative ease.
- Short Name / Acronym:
- Graphene U-Net
- Site Accession Number:
- 2021-023
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOEPrimary Award/Contract Number:AC02-05CH11231
- DOE Contract Number:
- AC02-05CH11231
- Code ID:
- 60277
- OSTI ID:
- code-60277
- Country of Origin:
- United States
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