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Published by Elsevier - Health Sciences Division, 2022
ISBN 10: 0323857833 ISBN 13: 9780323857833
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Taschenbuch. Condition: Neu. Deep Learning on Edge Computing Devices | Design Challenges of Algorithm and Architecture | Xichuan Zhou (u. a.) | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2022 | Elsevier Inc | EAN 9780323857833 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Add to basketCondition: New. Focuses on hardware architecture and embedded deep learning, including neural networks Brings together neural network algorithm and hardware design optimization approaches to deep learning, alongside real-world applications Consid.
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Language: English
Published by Elsevier Science & Technology, Elsevier, 2022
ISBN 10: 0323857833 ISBN 13: 9780323857833
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization.This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design.