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020			_a9783030567699
024	7		_a10.1007/978-3-030-56769-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1634 _b2021 EB
100	1		_aMery, Domingo _eautor _4http://id.loc.gov/vocabulary/relators/aut _9678849
245	1	0	_aComputer Vision for X-Ray Testing : _bImaging, Systems, Image Databases, and Algorithms _cby Domingo Mery, Christian Pieringer
250			_aSecond edition 2021
264		1	_aCham, Switzerland _bSpringer International Publising _c2021
300			_a1 recurso en línea (XXVI, 456 páginas) _b420 ilustraciones, 356 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
520	3		_aBuilding on its strengths as a uniquely accessible textbook combining computer vision and X-ray testing, this enhanced second edition now firmly addresses core developments in deep learning and vision, providing numerous examples and functions using the Python language. Covering complex topics in an easy-to-understand way, without requiring any prior knowledge in the field, the book provides a concise review of the key methodologies in computer vision for solving important problems in industrial radiology. The theoretical coverage is strengthened with easily written code examples that the reader can modify when developing new functions for X-ray testing. Topics and features: Describes the core techniques for image processing used in X-ray testing, including image filtering, edge detection, image segmentation and image restoration Incorporates advances in deep learning, including aspects regarding convolutional neural networks, transfer learning, and generative adversarial networks Provides more than 65 examples in Python, and is supported by an associated website, including a database of X-ray images and a freely available Matlab toolbox Includes new advances in simulation approaches for baggage inspection, simulated X-ray imaging, and simulated structures (such as defects and threat objects) Presents a range of different representations for X-ray images, explaining how these enable new features to be extracted from the original image Examines a range of known X-ray image classifiers and classification strategies, and techniques for estimating the accuracy of a classifier Reviews a variety of applications for X-ray testing, from industrial inspection and baggage screening to the quality control of natural products This classroom-tested and hands-on text/guidebook is ideal for advanced undergraduates, graduates, and professionals interested in practically applying image processing, pattern recognition and computer vision techniques for non-destructive quality testing and security inspection. Dr. Domingo Mery is a Full Professor at the Machine Intelligence Group (GRIMA) of the Department of Computer Sciences, and Director of Research and Innovation at the School of Engineering, at the Pontifical Catholic University of Chile, Santiago, Chile. Dr. Christian Pieringer is an Adjunct Instructor at the same institution.
988			_aSpringer_Computer_2021
650		7	_2embne _aVisión por ordenador _9159793
650		7	_2embne _9139975 _aRayos X _xAplicaciones industriales
700	1		_aPieringer, Christian _eautor _4http://id.loc.gov/vocabulary/relators/aut _9678850
710	2		_aSpringerLink
776	0	8	_iPrinted edition: _z9783030567682
776	0	8	_iPrinted edition: _z9783030567705
776	0	8	_iPrinted edition: _z9783030567712
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-56769-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2021 _dz _ek _zSI