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General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning by Liu, Y.; Sun, Q. M.; Lu, Dr. W. H.; Wang, Dr. H. L.; Sun, Y.; Wang, Z. T.; Lu, X.; Zeng, Prof. K. Y. is a scholarly article available to read on EtoBox.

What is General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning about?

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.

Author

Liu, Y.; Sun, Q. M.; Lu, Dr. W. H.; Wang, Dr. H. L.; Sun, Y.; Wang, Z. T.; Lu, X.; Zeng, Prof. K. Y.

Published

2018

Language

EN