Deep Learning for Chemical Image Recognition (DECIMER) - Python scripts
This project hosts the tools and networks written in python which aims to develop methods to employ deep learning to recognize and interpret chemical structures from images in the printed and online literature with the aim of re-discovering scientific facts about natural products and their meta-data.
The project is co-supervised by,
- Prof. Christoph Steinbeck, Friedrich Schiller University, Jena.
- Prof. Achim Zielesny, Westphalian University of Applied Sciences, Recklinghausen.
.
├── Ansible_Automation_Scripts/ # Scripts which can be used to create and delete instances using Ansible on Google cloud console
├── CNN_Networks/ # Convolutional Neural Networks (Working and early-stage scripts)
├── Networks/ # 3-Layer,4-Layer and 5-Layer perceptrons (Working scripts, Scripts used for optimization and early-stage scripts)
├── Slurm Scripts/ # Scripts used to deploy programs on slurm system in ARA
├── Tools/ # Small scripts written for data curation
├── LICENSE
├── Python_Requirements
└── README.md
- This project is licensed under the MIT License - see the LICENSE file for details