Machine learning and deep learning for smart agriculture and applications:
Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book il...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
c2023
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-83 DE-898 Volltext |
| Zusammenfassung: | Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies.Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape. |
| Beschreibung: | 1 Online-Ressource (xix, 257 Seiten) |
| ISBN: | 9781668499764 |
| DOI: | 10.4018/978-1-6684-9975-7 |
Internformat
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| 520 | |a Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies.Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape. | ||
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| doi_str_mv | 10.4018/978-1-6684-9975-7 |
| format | Electronic eBook |
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| id | DE-604.BV049327283 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:44:33Z |
| indexdate | 2024-08-24T01:07:01Z |
| institution | BVB |
| isbn | 9781668499764 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034588118 |
| oclc_num | 1401215881 |
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| owner_facet | DE-91 DE-BY-TUM DE-83 DE-898 DE-BY-UBR |
| physical | 1 Online-Ressource (xix, 257 Seiten) |
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| publisher | IGI Global |
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| spelling | Machine learning and deep learning for smart agriculture and applications Mohamamd Farukh Hashmi, Avinash G. Kesakr, editors Hershey, Pennsylvania IGI Global c2023 1 Online-Ressource (xix, 257 Seiten) txt rdacontent c rdamedia cr rdacarrier Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies.Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape. Agricultural innovations Agricultural industries Technological innovations Deep learning (Machine learning) Machine learning Kesakr, Avinash G. edt Hashmi, Mohamamd Farukh edt Erscheint auch als Druck-Ausgabe 9781668499757 Erscheint auch als Druck-Ausgabe 1668499754 https://doi.org/10.4018/978-1-6684-9975-7 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Machine learning and deep learning for smart agriculture and applications Agricultural innovations Agricultural industries Technological innovations Deep learning (Machine learning) Machine learning |
| title | Machine learning and deep learning for smart agriculture and applications |
| title_auth | Machine learning and deep learning for smart agriculture and applications |
| title_exact_search | Machine learning and deep learning for smart agriculture and applications |
| title_exact_search_txtP | Machine learning and deep learning for smart agriculture and applications |
| title_full | Machine learning and deep learning for smart agriculture and applications Mohamamd Farukh Hashmi, Avinash G. Kesakr, editors |
| title_fullStr | Machine learning and deep learning for smart agriculture and applications Mohamamd Farukh Hashmi, Avinash G. Kesakr, editors |
| title_full_unstemmed | Machine learning and deep learning for smart agriculture and applications Mohamamd Farukh Hashmi, Avinash G. Kesakr, editors |
| title_short | Machine learning and deep learning for smart agriculture and applications |
| title_sort | machine learning and deep learning for smart agriculture and applications |
| topic | Agricultural innovations Agricultural industries Technological innovations Deep learning (Machine learning) Machine learning |
| topic_facet | Agricultural innovations Agricultural industries Technological innovations Deep learning (Machine learning) Machine learning |
| url | https://doi.org/10.4018/978-1-6684-9975-7 |
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