Da: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Regno Unito
EUR 23,66
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Aggiungi al carrelloCondizione: Very Good. Used, some outer edges and corners have minor scuffs, cover has light scratches, some outer pages have shelf wear, book content is in like new condition.
Like new, never been used.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 320.
Da: Majestic Books, Hounslow, Regno Unito
EUR 91,06
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Aggiungi al carrelloCondizione: New. pp. 320 Illus.
Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 90,84
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Aggiungi al carrelloCondizione: New. pp. 320.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 163,87
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 163,85
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 180,30
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 180,67
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 183,50
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Da: moluna, Greven, Germania
EUR 180,46
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Aggiungi al carrelloGebunden. Condizione: New. Integrates computer vision, pattern recognition, and AIPresents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image.
Lingua: Inglese
Editore: Springer New York Feb 2005, 2005
ISBN 10: 0387212957 ISBN 13: 9780387212951
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 222,67
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Evolutionary computation is becoming increasingly important for computer vision and pattern recognition and provides a systematic way of synthesis and analysis of object detection and recognition systems. Incorporating 'learning' into recognition systems will enable these systems to automatically generate new features on the fly and cleverly select a good subset of features according to the type of objects and images to which they are applied.This unique monograph investigates evolutionary computational techniques--such as genetic programming, linear genetic programming, coevolutionary genetic programming and genetic algorithms--to automate the synthesis and analysis of object detection and recognition systems.The purpose of incorporating learning into the system design is to avoid the time-consuming process of feature generation and selection and to reduce the cost of building object detection and recognition systems.Researchers, professionals, engineers, and students working in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology will find this well-developed and organized volume an invaluable resource.