Handbook of research on deep learning techniques for cloud-based industrial IoT:
"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 artifi...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
2023.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "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"-- |
| Beschreibung: | 30 PDFs (432 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781668481004 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
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| 245 | 0 | 0 | |a Handbook of research on deep learning techniques for cloud-based industrial IoT |c edited by P. Swarnalatha, and S. Prabu. |
| 246 | 3 | |a Handbook of research on deep learning techniques for cloud-based industrial internet of things | |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c 2023. | |
| 300 | |a 30 PDFs (432 pages) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 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 learning approach -- 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-based messaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | |a "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"-- |c Provided by publisher. | ||
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 07/07/2023). | ||
| 650 | 0 | |a Cloud computing. | |
| 650 | 0 | |a Deep learning (Machine learning) | |
| 650 | 0 | |a Internet of things |x Industrial applications. | |
| 700 | 1 | |a Prabu, S. |d 1981- |e editor. | |
| 700 | 1 | |a Swarnalatha, P. |q (Purushotham) |d 1977- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 1668480980 |z 9781668480984 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-8098-4 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00311057 |
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| _version_ | 1816797087019302912 |
| adam_text | |
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| author2 | Prabu, S. 1981- Swarnalatha, P. (Purushotham) 1977- |
| author2_role | edt edt |
| author2_variant | s p sp p s ps |
| author_facet | Prabu, S. 1981- Swarnalatha, P. (Purushotham) 1977- |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | T - Technology |
| callnumber-label | TK5105 |
| callnumber-raw | TK5105.8857 .H36 2023e |
| callnumber-search | TK5105.8857 .H36 2023e |
| callnumber-sort | TK 45105.8857 H36 42023E |
| callnumber-subject | TK - Electrical and Nuclear Engineering |
| collection | ZDB-98-IGB |
| contents | 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 learning approach -- 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-based messaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security. |
| ctrlnum | (CaBNVSL)slc00004579 (OCoLC)1389870419 |
| dewey-full | 004.67/82 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004.67/82 |
| dewey-search | 004.67/82 |
| dewey-sort | 14.67 282 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-98-IGB-00311057 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:51:59Z |
| institution | BVB |
| isbn | 9781668481004 |
| language | English |
| oclc_num | 1389870419 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 30 PDFs (432 pages) Also available in print. |
| psigel | ZDB-98-IGB |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | IGI Global, |
| record_format | marc |
| spelling | Handbook of research on deep learning techniques for cloud-based industrial IoT edited by P. Swarnalatha, and S. Prabu. Handbook of research on deep learning techniques for cloud-based industrial internet of things Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, 2023. 30 PDFs (432 pages) text rdacontent electronic isbdmedia online resource rdacarrier 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 learning approach -- 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-based messaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security. Restricted to subscribers or individual electronic text purchasers. "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"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 07/07/2023). Cloud computing. Deep learning (Machine learning) Internet of things Industrial applications. Prabu, S. 1981- editor. Swarnalatha, P. (Purushotham) 1977- editor. IGI Global, publisher. Print version: 1668480980 9781668480984 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-8098-4 Volltext |
| spellingShingle | Handbook of research on deep learning techniques for cloud-based industrial IoT 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 learning approach -- 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-based messaging system for secure and private communication: using blockchain and double AES encryption -- Chapter 22. Artificial intelligence in cyber security. Cloud computing. Deep learning (Machine learning) Internet of things Industrial applications. |
| title | Handbook of research on deep learning techniques for cloud-based industrial IoT |
| title_alt | Handbook of research on deep learning techniques for cloud-based industrial internet of things |
| title_auth | Handbook of research on deep learning techniques for cloud-based industrial IoT |
| title_exact_search | Handbook of research on deep learning techniques for cloud-based industrial IoT |
| title_full | Handbook of research on deep learning techniques for cloud-based industrial IoT edited by P. Swarnalatha, and S. Prabu. |
| title_fullStr | Handbook of research on deep learning techniques for cloud-based industrial IoT edited by P. Swarnalatha, and S. Prabu. |
| title_full_unstemmed | Handbook of research on deep learning techniques for cloud-based industrial IoT edited by P. Swarnalatha, and S. Prabu. |
| title_short | Handbook of research on deep learning techniques for cloud-based industrial IoT |
| title_sort | handbook of research on deep learning techniques for cloud based industrial iot |
| topic | Cloud computing. Deep learning (Machine learning) Internet of things Industrial applications. |
| topic_facet | Cloud computing. Deep learning (Machine learning) Internet of things Industrial applications. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-8098-4 |
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