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-# Nf-as-a-metric-for-quantifying-and-improving-super-resolution-microscopy-image-reconstruction
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+# Nf-as-a-metric-for-quantifying-and-improving-super-resolution-microscopy-image-reconstruction
+The model is trained for 10 epochs with a batch size of 2. Overall, the model is trained for 500,000 iterations, with generation time step T = 200, learning rate 0.0001. 
+During theinference, generation time steps are set to T = 500. The naturalization of images is donewith the ImageJ Mosaic Suite plugin. 
+The implementation of CVDM can be found on the GitHub page (G. Della Maggiora, L. A. Croquevielle, N. Deshpande, H. Horsley, T. Heinis, A. Yaki-movich, Conditional variational diffusion models, https://github.com/casus/cvdm)2023. 
+Further information and documentation (including a guide on installation of the Mosaic Suite plugin) can be found in  MOSAIC group, MosaicSuite documentation, https://sbalzarinilab.org/MosaicSuiteDoc/index.html.