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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2021
ISBN 10: 3030666441 ISBN 13: 9783030666446
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 528 pages. 9.25x6.10x1.14 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, 2021
ISBN 10: 3030666441 ISBN 13: 9783030666446
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 13th International Conference on Intelligent Robotics and Applications, ICIRA 2020, held in Kuala Lumpur, Malaysia, in November 2020. The 45 full papers and 3 short papers were carefully reviewed and selected from 66 submissions. The accepted papers were grouped into various subtopics including Advanced Measurement and Machine Vision System; Automation; Human-Robot Interaction; Mobile Robots and Intelligent Autonomous System; Recent Trends in Computational Intelligence; Robot Design, and Development and Control.Due to the Corona pandemic ICIRA 2020 was held as a virtual event.
Taschenbuch. Zustand: Neu. Intelligent Robotics and Applications | 13th International Conference, ICIRA 2020, Kuala Lumpur, Malaysia, November 5-7, 2020, Proceedings | Chee Seng Chan (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xii | Englisch | 2021 | Springer | EAN 9783030666446 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 560 | Sprache: Englisch | Produktart: Bücher | This book constitutes the proceedings of the 13th International Conference on Intelligent Robotics and Applications, ICIRA 2020, held in Kuala Lumpur, Malaysia, in November 2020. The 45 full papers and 3 short papers were carefully reviewed and selected from 66 submissions. The accepted papers were grouped into various subtopics including Advanced Measurement and Machine Vision System; Automation; Human-Robot Interaction; Mobile Robots and Intelligent Autonomous System; Recent Trends in Computational Intelligence; Robot Design, and Development and Control.Due to the Corona pandemic ICIRA 2020 was held as a virtual event.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 152,11
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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2018
ISBN 10: 3662571528 ISBN 13: 9783662571521
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Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2017
ISBN 10: 3662536900 ISBN 13: 9783662536902
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In den WarenkorbGebunden. Zustand: New.
Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Singapore|Springer, 2024
ISBN 10: 9811975566 ISBN 13: 9789811975561
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Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9811975531 ISBN 13: 9789811975530
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Taschenbuch. Zustand: Neu. Digital Watermarking for Machine Learning Model | Techniques, Protocols and Applications | Lixin Fan (u. a.) | Taschenbuch | xvi | Englisch | 2024 | Springer | EAN 9789811975561 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 281 pages. 9.50x6.25x1.00 inches. In Stock.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 275,33
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In den WarenkorbHardcover. Zustand: Brand New. 241 pages. 9.25x6.10x0.79 inches. In Stock.