國立虎尾科技大學 |

Handbook of research on deep learning techniques for cloud-based industrial IoT

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Handbook of research on deep learning techniques for cloud-based industrial IoT/ edited by P. Swarnalatha, and S. Prabu.
其他題名:	Handbook of research on deep learning techniques for cloud-based industrial internet of things
其他作者:	Prabu, S.,
出版者:	Hershey, Pennsylvania :IGI Global, : 2023.,
面頁冊數:	1 online resource (432 p.)
標題:	Cloud computing. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-8098-4
ISBN:	9781668481004

Handbook of research on deep learning techniques for cloud-based industrial IoT
Handbook of research on deep learning techniques for cloud-based industrial IoT[electronic resource] /Handbook of research on deep learning techniques for cloud-based industrial internet of thingsedited by P. Swarnalatha, and S. Prabu. - Hershey, Pennsylvania :IGI Global,2023. - 1 online resource (432 p.)

Includes bibliographical references and index.

Chapter 1. Artificial intelligence in video surveillance -- Chapter 2. Content-based video retrieval with temporal localization using a deep bimodal fusion approach -- Chapter 3. Artificial intelligence of things for smart healthcare development: an experimental review -- Chapter 4. Cloud-based intelligent virtual try-on using augmented reality -- Chapter 5. Insulator fault detection from UAV images using YOLOv5 -- Chapter 6. Blockchain-based deep learning approach for Alzheimer's disease classification -- Chapter 7. Intrusion detection on NF-bot-IoT dataset using artificial intelligence techniques -- Chapter 8. Real-time object detection and audio output system for blind users: using YOLOv3 algorithm and 360 degree camera sensor -- Chapter 9. Role of IoT technologies in agricultural ecosystems -- Chapter 10. Applications of deep learning in robotics -- Chapter 11. A multicloud-based deep learning model for smart agricultural applications-- Chapter 12. Automated MP3 tag editor via data mining: a classification software for predicting MP3 metadata -- Chapter 13. Machine learning-integrated IoT-based smart home energy management system -- Chapter 14. Generating complex animated characters of various art styles with optimal beauty scores using deep generative adversarial networks -- Chapter 15. Cloud-based TPA auditing with risk prevention -- Chapter 16. Detection and classification of dense tomato fruits by integrating coordinate attention mechanism with YOLO model -- Chapter 17. A study on an internet of things (IoT)-enabled smart solar grid system -- Chapter 18. Accuracy determination: an enhanced intrusion detection system using deep learningapproach -- Chapter 19. IoT-based smart accident detection and alert system -- Chapter 20. Revolutionizing the farm-to-table journey: a comprehensive review of blockchain technology in agriculture supply chain -- Chapter 21. Blockchain-basedmessaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security.

"Deep Learning Techniques for Cloud-Based Industrial IoT aims to demonstrate how computer scientists and engineers of today might employ artificial intelligence in practical applications with the emerging cloud and IoT technologies.The book also gathers recent research works in emerging artificial intelligence methods and applications for processing and storing the data generated from the cloud-based Internet of Things. Covering key topics such as data, cybersecurity,blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, engineers, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students"--

ISBN: 9781668481004Subjects--Topical Terms:

716205
Cloud computing.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: TK5105.8857 / .H36 2023e

Dewey Class. No.: 004.67/82

Handbook of research on deep learning techniques for cloud-based industrial IoT
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505 0 $a Chapter 1. Artificial intelligence in video surveillance -- Chapter 2. Content-based video retrieval with temporal localization using a deep bimodal fusion approach -- Chapter 3. Artificial intelligence of things for smart healthcare development: an experimental review -- Chapter 4. Cloud-based intelligent virtual try-on using augmented reality -- Chapter 5. Insulator fault detection from UAV images using YOLOv5 -- Chapter 6. Blockchain-based deep learning approach for Alzheimer's disease classification -- Chapter 7. Intrusion detection on NF-bot-IoT dataset using artificial intelligence techniques -- Chapter 8. Real-time object detection and audio output system for blind users: using YOLOv3 algorithm and 360 degree camera sensor -- Chapter 9. Role of IoT technologies in agricultural ecosystems -- Chapter 10. Applications of deep learning in robotics -- Chapter 11. A multicloud-based deep learning model for smart agricultural applications-- Chapter 12. Automated MP3 tag editor via data mining: a classification software for predicting MP3 metadata -- Chapter 13. Machine learning-integrated IoT-based smart home energy management system -- Chapter 14. Generating complex animated characters of various art styles with optimal beauty scores using deep generative adversarial networks -- Chapter 15. Cloud-based TPA auditing with risk prevention -- Chapter 16. Detection and classification of dense tomato fruits by integrating coordinate attention mechanism with YOLO model -- Chapter 17. A study on an internet of things (IoT)-enabled smart solar grid system -- Chapter 18. Accuracy determination: an enhanced intrusion detection system using deep learningapproach -- Chapter 19. IoT-based smart accident detection and alert system -- Chapter 20. Revolutionizing the farm-to-table journey: a comprehensive review of blockchain technology in agriculture supply chain -- Chapter 21. Blockchain-basedmessaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security.
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