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Titlebook: Computer Vision for X-Ray Testing; Imaging, Systems, Im Domingo Mery,Christian Pieringer Textbook 2021Latest edition Springer Nature Switze

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Simulation in X-ray Testing,Networks (GANs) in the simulation of realistic X-ray images. Finally, we present ‘aRTist’, a simulation software that can be used to generate very realistic X-ray images. The chapter also has some Python examples that the reader can run and follow easily.
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Textbook 2021Latest editionom industrial inspection and baggage screening to the quality control of natural products; provides supporting material at an associated website, including a database of X-ray images and a Matlab toolbox for use with the book’s many examples.
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X-ray Testing,ndetectable to the naked eye. Thus, X-ray testing is used to determine if a test object deviates from a given set of specifications. Typical applications are the inspection of automotive parts, quality control of welds, baggage screening, analysis of food products, inspection of cargos, and quality
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Images for X-ray Testing,. The images are organized in a public database called .ray+that can be used free of charge, but for research and educational purposes only. The database includes five groups of X-ray images: castings, welds, baggage, natural objects, and settings. Each group has several series, and each series seve
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Geometry in X-ray Testing, view geometry which is normally used in X-ray computer vision systems. The chapter describes an explicit model which relates the 3D coordinates of an object to the 2D coordinates of the digital X-ray image pixel, the calibration problem, the geometric and algebraic constraints between two, three, a
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Deep Learning in X-ray Testing,ith features that are . efficiently using a hierarchical feature extraction approach. Usually, the learned features are so discriminative that no sophisticated classifiers are required. In last years, deep learning has been successfully used in image and video recognition, and it has been establishe
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