Abstract
Data processing has always been a part of transmission electron microscopy (TEM) image and spectroscopy analysis. In this chapter, the authors revisit the historical aspect of image/data processing, understand the basic concepts of machine learning (ML), open-source tools available, select applications, future needs, and limitations. Image simulations and processing form an integral part of our ability to decipher TEM/scanning transmission electron microscopy (STEM) data with confidence. The authors present the fundamentals behind the image processing and simulations as they are now being accomplished using ML applications. One of the other major challenges facing in-situ TEM/STEM measurements is to save, transfer, and store large datasets at the rate they are generated. In the last several years, AI and ML have taken central stage in the development of science and engineering applications, from automatic control systems to data processing and image recognition.
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