Multi-Output CNN for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data
Code and example use of a trained CNN for extracting single- and bi-exponential parameters that describe optoelectronic dynamics of interest in semiconducting materials as measured by trEFM.
This repository is meant to accompany the paper published: (insert link here).
Breshears, M.D., Giridharagopal, R., Ginger, D.S. Multi-Output Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data. Submitted. 2025. https://doi.org/10.48550/arXiv.2502.03572.
Download the .py and .ipynb files from this repository.
Due to size constraints, the trained model state dictionary cannot be uploaded to Github. You can request the best_model.pth file and example data (as shown in the example_use.ipynb file) from the corresponding author.