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Published by Engineering Science Reference, 2020
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 316 | Sprache: Englisch | Produktart: Bücher | The agricultural sector can benefit immensely from developments in the field of smart farming. However, this research area focuses on providing specific fixes to particular situations and falls short on implementing data-driven frameworks that provide large-scale benefits to the industry as a whole. Using deep learning can bring immense data and improve our understanding of various earth sciences and improve farm services to yield better crop production and profit. Smart Agricultural Services Using Deep Learning, Big Data, and IoT is an essential publication that focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is ideally designed for engineers, programmers, software developers, agriculturalists, farmers, policymakers, researchers, academicians, and students.
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Published by Engineering Science Reference, 2020
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is designed for engineers, programmers, software developers, agriculturalists.
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Published by Engineering Science Reference, 2020
ISBN 10: 179985485X ISBN 13: 9781799854852
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Taschenbuch. Condition: Neu. Smart Agricultural Services Using Deep Learning, Big Data, and IoT | Amit Kumar Gupta (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2020 | Engineering Science Reference | EAN 9781799854852 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Published by Engineering Science Reference, 2020
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Published by Engineering Science Reference, 2020
ISBN 10: 179985003X ISBN 13: 9781799850038
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is designed for engineers, programmers, software developers, agriculturalists.
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Published by Engineering Science Reference, 2020
ISBN 10: 179985485X ISBN 13: 9781799854852
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'This book explores the application of deep learning, big data, IoT in agricultural services'.
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Published by Engineering Science Reference, 2020
ISBN 10: 179985003X ISBN 13: 9781799850038
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Buch. Condition: Neu. Smart Agricultural Services Using Deep Learning, Big Data, and IoT | Amit Kumar Gupta (u. a.) | Buch | Gebunden | Englisch | 2020 | Engineering Science Reference | EAN 9781799850038 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Published by Engineering Science Reference, 2020
ISBN 10: 179985003X ISBN 13: 9781799850038
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The agricultural sector can benefit immensely from developments in the field of smart farming. However, this research area focuses on providing specific fixes to particular situations and falls short on implementing data-driven frameworks that provide large-scale benefits to the industry as a whole. Using deep learning can bring immense data and improve our understanding of various earth sciences and improve farm services to yield better crop production and profit. Smart Agricultural Services Using Deep Learning, Big Data, and IoT is an essential publication that focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is ideally designed for engineers, programmers, software developers, agriculturalists, farmers, policymakers, researchers, academicians, and students.