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.
@article{arxiv.1809.03704,
title = {General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning},
author = {Y. Liu and Q. M. Sun and Dr. W. H. Lu and Dr. H. L. Wang and Y. Sun and Z. T. Wang and X. Lu and Prof. K. Y. Zeng},
journal= {arXiv preprint arXiv:1809.03704},
year = {2018}
}