Computer Vision and Machine Learning in Agriculture, Volume 2 (Algorithms for Intelligent Systems) - Tapa blanda

9789811699931: Computer Vision and Machine Learning in Agriculture, Volume 2 (Algorithms for Intelligent Systems)

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ISBN 10: 9811699933 ISBN 13: 9789811699931

Editorial: Springer, 2023

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EditorialSpringer
A�o de publicaci�n2023
ISBN 10 9811699933
ISBN 13 9789811699931
Encuadernaci�nTapa blanda
IdiomaIngl�s
N�mero de edici�n1
N�mero de p�ginas276
EditorUddin Mohammad Shorif, Bansal Jagdish Chand

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Computer Vision and Machine Learning in Agriculture, Volume 2

Publicado por Springer, Berlin|Springer Nature Singapore|Springer, 2023

ISBN 10: 9811699933 ISBN 13: 9789811699931

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Kartoniert / Broschiert. Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is as an extension of previous book Computer Vision and Machine Learning in Agriculture for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by renderi. N� de ref. del art�culo: 822917095

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Computer Vision and Machine Learning in Agriculture, Volume 2

Jagdish Chand Bansal

Publicado por Springer Nature Singapore Mrz 2023, 2023

ISBN 10: 9811699933 ISBN 13: 9789811699931

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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

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Taschenbuch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is as an extension of previous book 'Computer Vision and Machine Learning in Agriculture' for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies. 276 pp. Englisch. N� de ref. del art�culo: 9789811699931

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Computer Vision and Machine Learning in Agriculture, Volume 2 (Algorithms for Intelligent Systems)

Publicado por Springer, 2023

ISBN 10: 9811699933 ISBN 13: 9789811699931

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Librería: Ria Christie Collections, Uxbridge, Reino Unido

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Computer Vision and Machine Learning in Agriculture, Volume 2

Jagdish Chand Bansal

Publicado por Springer Nature Singapore, Springer Nature Singapore, 2023

ISBN 10: 9811699933 ISBN 13: 9789811699931

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Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is as an extension of previous book 'Computer Vision and Machine Learning in Agriculture' for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies. N� de ref. del art�culo: 9789811699931

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