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

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

In recent years, convolutional neural network (CNN)-based methods have shown remarkable performance in the denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the main focus of existing studies. Recently, however, an alternative and highly competitive deep learning architecture, ...

Type: Python

Creator: Zafran Hussain Shah

Submitter: Zafran Hussain Shah

DOI: 10.48546/workflowhub.workflow.675.1

Created: 21st Nov 2023 at 09:02, Last updated: 21st Nov 2023 at 10:28

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

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