  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.
