General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning
Abstract
This paper develops a resolution enhancement method for post-processing the images from Atomic Force Microscopy (AFM). This method is based on deep learning neural networks in the AFM topography measurements. In this study, a very deep convolution neural network is developed to derive the high-resolution topography image from the low-resolution topography image. The AFM measured images from various materials are tested in this study. The derived high-resolution AFM images are comparable with the experimental measured high-resolution images measured at the same locations. The results suggest that this method can be developed as a general post-processing method for AFM image analysis.
- Publication:
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arXiv e-prints
- Pub Date:
- September 2018
- DOI:
- 10.48550/arXiv.1809.03704
- arXiv:
- arXiv:1809.03704
- Bibcode:
- 2018arXiv180903704L
- Keywords:
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- Physics - Data Analysis;
- Statistics and Probability;
- Condensed Matter - Materials Science
- E-Print:
- 14 pages, 4 figures 1 table