Review: Deep Learning in Electron Microscopy

09/17/2020
by   Jeffrey M. Ede, et al.
0

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.

READ FULL TEXT

page 2

page 3

page 4

page 5

page 18

page 23

page 26

page 32

research
11/17/2018

Cross-modality deep learning brings bright-field microscopy contrast to holography

Deep learning brings bright-field microscopy contrast to holographic ima...
research
03/08/2021

Model Complexity of Deep Learning: A Survey

Model complexity is a fundamental problem in deep learning. In this pape...
research
10/08/2020

Free annotated data for deep learning in microscopy? A hitchhiker's guide

In microscopy, the time burden and cost of acquiring and annotating larg...
research
08/05/2020

Machine learning for faster and smarter fluorescence lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique ...
research
01/04/2021

Advances in Electron Microscopy with Deep Learning

This doctoral thesis covers some of my advances in electron microscopy w...
research
08/05/2020

Global Voxel Transformer Networks for Augmented Microscopy

Advances in deep learning have led to remarkable success in augmented mi...
research
06/12/2023

A Brief Review of Hypernetworks in Deep Learning

Hypernetworks, or hypernets in short, are neural networks that generate ...

Please sign up or login with your details

Forgot password? Click here to reset