Deep learning in electron microscopy

Author:

Ede Jeffrey MORCID

Abstract

Abstract Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy.

Funder

Engineering and Physical Sciences Research Council

Publisher

IOP Publishing

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Reference1654 articles.

1. There’s plenty of room at the top: what will drive computer performance after Moore’s law?;Leiserson;Science,2020

2. Revisiting unreasonable effectiveness of data in deep learning era;Sun,2017

3. Machine learning and big scientific data;Hey;Phil. Trans. R. Soc. A,2020

4. A review of deep learning with special emphasis on architectures, applications and recent trends;Sengupta;Knowl.-Based Syst.,2020

5. Review of deep learning algorithms and architectures;Shrestha;IEEE Access,2019

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