PyNNcml

A python toolbox based on PyTorch which utilized neural network for rain estimation and classification from commercial microwave link (CMLs) data. This toolbox provides an implementation of algorithms for extracting rain-rate using neural networks and CMLs. Addinaly this project provides an example dataset with data from two CMLs and implementation of performance and robustness metrics.

This project was initially create as part of the M.Sc. thesis of Hai Victor Habi, under the supervision of Prof. Hagit Messer at Tel Aviv University. Now this project is maintained by Hai Victor Habi and the Cellular Environmental Monitoring and Processing Lab at Tel Aviv University.

To use it please start with https://github.com/haihabi/PyNNcml/tree/main/examples