Titlebook: Data Science for Nano Image Analysis; Chiwoo Park,Yu Ding Book 2021 Springer Nature Switzerland AG 2021 Nano Image Analysis.Data Science.M

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Change Point Detection,serve the transformation of nanoscale objects as it occurs is unparalleled in comparison to other material characterization methods, and is of tremendous value to material scientists and engineers who study matter at nanoscale dimensions. One important task in such effort is to detect changes in the

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Multi-Object Tracking Analysis,contain the structures of material objects that change over the course of a material process. If one is interested in knowing how a population of material objects is collectively evolved in their sizes and shapes, a probability distribution function of the shapes and sizes ought to be tracked. Towar

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Super Resolution,nd the effort intensifies greatly in the past two decades. The essential objective of super-resolution is to enhance the quality of a low-resolution image, using a high-resolution counterpart. The super-resolution research started with combining information content from multiple low-resolution image

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Chain Maps and Reduction Algorithmsentation for material images, as the subsequent image analyses after segmentation are to be discussed in the latter chapters. In the first section of this chapter, we describe the unique characteristics of material images and the challenges that they cause in image segmentation. In the second sectio

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Prologue

Prospects in Digital Image Processingference. We want to note that the importance of material mixing applies not only to nanoparticle-embedded materials but also to other types of material mixing involving a host and additive or reinforcing agents, endowing the methods discussed in this chapter with broader impacts beyond nanomaterials

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Prospects in Digital Image Processingi-stage growth process, a nonparametric approach is inevitable. As such, the online tracking problem discussed in this chapter becomes the data science problem of modeling, estimating, and updating of a nonparametric, time-varying probability density distribution.

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