Review: Deep Learning in Electron Microscopy
It serves as an introductory resource for developers in electron microscopy, but is incremental as it synthesizes existing knowledge without presenting new research.
This review paper provides a practical guide for developers with limited familiarity on applying deep learning in electron microscopy, covering popular applications, necessary hardware and software, neural network components, architectures, optimization, and future directions.
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. Afterwards, 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.