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Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data.

Zafran Hussain ShahMarcel MüllerWolfgang HübnerTung-Cheng WangDaniel TelmanThomas HuserWolfram Schenck
Published in: GigaScience (2024)
The SwinT-fairSIM method is well suited for denoising SR-SIM images. By fine-tuning, already trained models can be easily adapted to different noise characteristics and cell structures. Furthermore, the provided datasets are structured in a way that the research community can readily use them for research on denoising, super-resolution, and transfer learning strategies.
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