This repository contains all data relevant for the PhD thesis "Spatio-Temporal Interface Reconstruction by Means of Glare Points and Deep Learning" by Maximilian Dreisbach that has not been previously published elsewhere.
This includes image data from experiments and the weights of neural networks trained for the spatio-temporal reconstruction of the gas-liquid interface on the basis of this measurement data. In particular glare-point shadowgraphy experiments involving droplet impingement on patterned substrates and the respective trained networks can be found in this repository.