What is it about?
We have shown with a home-made Raman microscope with AI that reinforcement learning adaptively feeds back “optimal” illumination pattern during the measurement to detect the existence of anomaly, allowing faster measurements while guaranteeing accuracy.
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Why is it important?
To accelerate the measurement is by measuring necessary parts with a suitable number of illumination points. However, how to design these points during measurement remains a challenge. Machine learning applied on the fly can tell us how to do.
Perspectives
The proposed algorithm can be applied to other types of microscopy that can control measurement condition on the fly, offering a new approach for the acceleration of accurate measurements in various applications.
Tamiki Komatsuzaki
Hokkaido Daigaku
Read the Original
This page is a summary of: On-the-fly Raman microscopy guaranteeing the accuracy of discrimination, Proceedings of the National Academy of Sciences, March 2024, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2304866121.
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