TL;DR
This review explains how deep learning is revolutionizing electron microscopy by covering applications, necessary tools, neural network components, architectures, and future prospects for researchers and developers.
Contribution
It provides a comprehensive, practical overview tailored for developers new to applying deep learning in electron microscopy, including hardware, software, and neural network insights.
Findings
Deep learning enhances image analysis in electron microscopy.
Guidelines for hardware and software setup are provided.
Future research directions are discussed.
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. 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.
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