Three trained models for an emitter density of 4, 6 and 9 emitters / µm^2 to be supplied to the CNN architecture published by Nehme et al.
For using the trained networks, please refer to the manual on usage of the CNN (in Python, GPU accelerated) by Elias Nehme, Lucien E. Weiss, Tomer Michaeli, and Yoav Shechtman, "Deep-STORM: super-resolution single-molecule microscopy by deep learning," Optica 5, 458-464 (2018).
When using any of the supplied information, please refer to our publication: R. Barth, K. Bystricky, H. A. Shaban, Coupling chromatin structure and dynamics by live super-resolution imaging. Sci. Adv. 6, eaaz2196 (2020).