DL4MicEverywhere / dfcan-zerocostdl4mic / 1.14.1

dfcan-zerocostdl4mic implementation.

Super-resolution via super-pixelisation. Deep Fourier channel attention network (DFCAN) is a network created to transform low-resolution (LR) images to super-resolved (SR) images, published by Qiao, Chang and Li, Di and Guo, Yuting and Liu, Chong and Jiang, Tao and Dai, Qionghai and Li, Dong. The training is done using LR-SR image pairs, taking the LR images as input and obtaining an output as close to SR as posible.
Tags
AMD64colabnotebookdenoisingZeroCostDL4Mic
Citation
https://doi.org/10.1038/s41467-021-22518-0von Chamier, L., Laine, R.F., Jukkala, J. et al. Democratising deep learning for microscopy with ZeroCostDL4Mic. Nat Commun 12, 2276 (2021). https://doi.org/10.1038/s41467-021-22518-0
https://doi.org/10.1038/s41592-020-01048-5Qiao C, Li D, Guo Y, Liu C, Jiang T, Dai Q, Li D. Evaluation and development of deep neural networks for image super-resolution in optical microscopy. Nat Methods. 2021 Feb;18(2):194-202. doi: 10.1038/s41592-020-01048-5. Epub 2021 Jan 21. PMID: 33479522.
Solution written by
DL4MicEverywhere team
album team

Arguments

--path
What is your working path? (default value: .)

Usage instructions

Please follow this link for details on how to install and run this solution.