Catching up with deep learning in spectral imaging

Having a deeper insight into deep learning is beneficial.
Catching up with deep learning in spectral imaging
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Deep learning continues to show its power for science and applications. Spectral imaging is not an exception. Besides us, there must be many other peers who are also getting involved in the trend of developing spectral imaging with deep learning. Having an overview of these precious contributions is equally beneficial. 

If you are interested in our work, please refer to the review “Spectral imaging with deep learning” published in Light: Science & Applications following the link: https://www.nature.com/articles/s41377-022-00743-6. Alternatively, you may reach me via my email address: haox@zju.edu.cn

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Electrical and Electronic Engineering
Technology and Engineering > Electrical and Electronic Engineering