Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9786630469592
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9786630469592
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Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. In the digital era, logos play a crucial role in establishing brand identity, consumer trust, and product authenticity. However, the increasing availability of sophisticated image-editing tools has made it easier to create and distribute counterfeit or manipulated logos. Detecting fake logos accurately and efficiently has therefore become an important application of Artificial Intelligence, Computer Vision, and Deep Learning. Fake Logo Detection Using CNN Models: A Deep Learning Approach to Brand Authentication presents a practical and research-oriented approach to identifying genuine and counterfeit logos using Convolutional Neural Network (CNN) models. The book introduces the fundamentals of image processing, computer vision, deep learning, and CNN architectures before progressing toward the design and implementation of an automated logo authentication system. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9786630469592
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 72 pp. Englisch. N° de réf. du vendeur 9786630469592
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. N° de réf. du vendeur 9786630469592
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. In the digital era, logos play a crucial role in establishing brand identity, consumer trust, and product authenticity. However, the increasing availability of sophisticated image-editing tools has made it easier to create and distribute counterfeit or manipulated logos. Detecting fake logos accurately and efficiently has therefore become an important application of Artificial Intelligence, Computer Vision, and Deep Learning. Fake Logo Detection Using CNN Models: A Deep Learning Approach to Brand Authentication presents a practical and research-oriented approach to identifying genuine and counterfeit logos using Convolutional Neural Network (CNN) models. The book introduces the fundamentals of image processing, computer vision, deep learning, and CNN architectures before progressing toward the design and implementation of an automated logo authentication system. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786630469592
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware 72 pp. Englisch. N° de réf. du vendeur 9786630469592
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Fake Logo Detection Using CNN Models | A Deep Learning Approach to Brand Authentication | K. Viswanath Allamraju (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630469592 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 138079283
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