Review: Deep Learning in Electron Microscopy
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 9; 2023: 2; 2024: 2; 2025: 2; 2026: 2.
20 papers.
Sort:
- 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Datacited by 108
- 2022Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopycited by 19
- 2023Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy imagescited by 8
- 2021An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analyticscited by 7
- 2022Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patternscited by 7
- 2022Segmentation in large-scale cellular electron microscopy with deep learning: A literature surveycited by 6
- 2022Data-driven Science and Machine Learning Methods in Laser-Plasma Physicscited by 4
- 2021An End-to-End Computer Vision Methodology for Quantitative Metallographycited by 3
- 2021Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Datacited by 3
- 2022Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy imagescited by 2
- 2022Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflowscited by 2
- 2022SAIBench: Benchmarking AI for Sciencecited by 1
8 more
- 2022Ensemble of Pre-Trained Neural Networks for Segmentation and Quality Detection of Transmission Electron Microscopy Imagescited by 0
- 2022Interpreting deep learning output for out-of-distribution detectioncited by 0
- 2024Zero-Shot Image Denoising for High-Resolution Electron Microscopycited by 0
- 2024Machine learning meets mass spectrometry: a focused perspectivecited by 0
- 20254D-PreNet: A Unified Preprocessing Framework for 4D-STEM Data Analysiscited by 0
- 2025Contrast transfer functions help quantify neural network out-of-distribution generalization in HRTEMcited by 0
- 2026Atomic Depth Estimation From Noisy Electron Microscopy Data Via Deep Learningcited by 0
- 2026Physics Informed Generative AI Enabling Labour Free Segmentation For Microscopy Analysiscited by 0
- 2026Physics Informed Generative AI Enabling Labour Free Segmentation For Microscopy Analysis2 Feb 2026
- 2026Atomic Depth Estimation From Noisy Electron Microscopy Data Via Deep Learning20 Jan 2026
- 2025Contrast transfer functions help quantify neural network out-of-distribution generalization in HRTEM9 Dec 2025
- 20254D-PreNet: A Unified Preprocessing Framework for 4D-STEM Data Analysis5 Aug 2025
- 2024Machine learning meets mass spectrometry: a focused perspective27 Jun 2024
- 2024Zero-Shot Image Denoising for High-Resolution Electron Microscopy20 Jun 2024
- 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Data30 May 2023
- 2023Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images18 Jan 2023
- 2022Data-driven Science and Machine Learning Methods in Laser-Plasma Physics30 Nov 2022
- 2022Interpreting deep learning output for out-of-distribution detection7 Nov 2022
- 2022Ensemble of Pre-Trained Neural Networks for Segmentation and Quality Detection of Transmission Electron Microscopy Images5 Sep 2022
- 2022Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows4 Aug 2022
8 more
- 2022Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey14 Jun 2022
- 2022SAIBench: Benchmarking AI for Science11 Jun 2022
- 2022Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy images25 Mar 2022
- 2022Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns1 Feb 2022
- 2022Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy8 Jan 2022
- 2021An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics30 Sep 2021
- 2021Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Data21 Jul 2021
- 2021An End-to-End Computer Vision Methodology for Quantitative Metallography22 Apr 2021
- 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Datacited by 108
- 2022Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopycited by 19
- 2023Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy imagescited by 8
- 2021An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analyticscited by 7
- 2022Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patternscited by 7
- 2022Segmentation in large-scale cellular electron microscopy with deep learning: A literature surveycited by 6
- 2022Data-driven Science and Machine Learning Methods in Laser-Plasma Physicscited by 4
- 2021An End-to-End Computer Vision Methodology for Quantitative Metallographycited by 3
- 2021Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Datacited by 3
- 2022Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy imagescited by 2
- 2022Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflowscited by 2
- 2022SAIBench: Benchmarking AI for Sciencecited by 1
12 most cited of 20 All 20 (JSON)
- 2026Physics Informed Generative AI Enabling Labour Free Segmentation For Microscopy Analysis2 Feb 2026
- 2026Atomic Depth Estimation From Noisy Electron Microscopy Data Via Deep Learning20 Jan 2026
- 2025Contrast transfer functions help quantify neural network out-of-distribution generalization in HRTEM9 Dec 2025
- 20254D-PreNet: A Unified Preprocessing Framework for 4D-STEM Data Analysis5 Aug 2025
- 2024Machine learning meets mass spectrometry: a focused perspective27 Jun 2024
- 2024Zero-Shot Image Denoising for High-Resolution Electron Microscopy20 Jun 2024
- 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Data30 May 2023
- 2023Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images18 Jan 2023
- 2022Data-driven Science and Machine Learning Methods in Laser-Plasma Physics30 Nov 2022
- 2022Interpreting deep learning output for out-of-distribution detection7 Nov 2022
- 2022Ensemble of Pre-Trained Neural Networks for Segmentation and Quality Detection of Transmission Electron Microscopy Images5 Sep 2022
- 2022Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows4 Aug 2022
12 newest of 20 All 20 (JSON)