Abstract
We propose Differentiable Microscopy, a machine-learning-driven optical system design paradigm, that may invent new unconventional microscope designs using carefully curated data. We demonstrate Quantitative Phase Microscopy, and Confocal Microscopy as use cases.
© 2023 The Author(s)
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