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Applications of machine learning in ...
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Alsamhi, Saeed, (1985-)
Applications of machine learning in UAV networks
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Applications of machine learning in UAV networksJahan Hassan, Saeed Alsamhi, editors.
其他題名:
Applications of machine learning in unmanned aerial vehicles networks
其他作者:
Alsamhi, Saeed,
出版者:
Hershey, Pennsylvania :IGI Global,2024.
面頁冊數:
1 online resource (406 p.)
標題:
Drone aircraftControl systems.
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-0578-2
ISBN:
9798369305805$q(ebook)
Applications of machine learning in UAV networks
Applications of machine learning in UAV networks
[electronic resource] /Applications of machine learning in unmanned aerial vehicles networksJahan Hassan, Saeed Alsamhi, editors. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (406 p.)
Includes bibliographical references and index.
Chapter 1. The role of machine learning in UAV-assisted communication -- Chapter 2. DRL-based coverage optimization in UAV networks for microservice-based IoT applications -- Chapter 3. Applications of machine learning in UAV-based detecting and tracking objects: analysis and overview -- Chapter 4. Applications ML in UAVs-based detecting and tracking objects and people -- Chapter 5. Monitoring of wildlife using unmanned aerial vehicle (UAV) with machine learning -- Chapter 6. Integration of unmanned aerial vehicle systems with machine learning algorithms for wildlife monitoring and conservation -- Chapter 7. Machine learning and deep learning-based prediction and monitoring of forest fires using unmanned aerial vehicle -- Chapter 8. Comprehensive framework for control and coordination of UAV swarms in wildfire management -- Chapter 9. Machine learning in UAV-assisted smart farming -- Chapter 10. Applicability of UAV in crop health monitoring using machine learning techniques -- Chapter 11. UAV-based warehouse management using multi-agent RL: applications, challenges, and solutions -- Chapter 12. Enhancing medical services through machine learning and UAV technology: applications and Benefits.
"Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy.This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond."--
ISBN: 9798369305805$q(ebook)Subjects--Topical Terms:
492279
Drone aircraft
--Control systems.Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: TL589.4 / .A67 2024e
Dewey Class. No.: 629.1326
Applications of machine learning in UAV networks
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Chapter 1. The role of machine learning in UAV-assisted communication -- Chapter 2. DRL-based coverage optimization in UAV networks for microservice-based IoT applications -- Chapter 3. Applications of machine learning in UAV-based detecting and tracking objects: analysis and overview -- Chapter 4. Applications ML in UAVs-based detecting and tracking objects and people -- Chapter 5. Monitoring of wildlife using unmanned aerial vehicle (UAV) with machine learning -- Chapter 6. Integration of unmanned aerial vehicle systems with machine learning algorithms for wildlife monitoring and conservation -- Chapter 7. Machine learning and deep learning-based prediction and monitoring of forest fires using unmanned aerial vehicle -- Chapter 8. Comprehensive framework for control and coordination of UAV swarms in wildfire management -- Chapter 9. Machine learning in UAV-assisted smart farming -- Chapter 10. Applicability of UAV in crop health monitoring using machine learning techniques -- Chapter 11. UAV-based warehouse management using multi-agent RL: applications, challenges, and solutions -- Chapter 12. Enhancing medical services through machine learning and UAV technology: applications and Benefits.
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"Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy.This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond."--
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-0578-2
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