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Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy

By Chenyu Qiao and others at
LogoTsinghua University
Computational super-resolution (SR) methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding SR performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells.... Show more
May 16, 2024
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Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy
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