Futuristic e-governance security with deep learning applications:
"In today's rapidly advancing digital world, governments face the dual challenge of harnessing technology to enhance security systems while safeguarding sensitive data from cyber threats and privacy breaches. Futuristic e-Governance Security With Deep Learning Applications provides a timel...
Gespeichert in:
Weitere Verfasser: | , , , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
2024.
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | "In today's rapidly advancing digital world, governments face the dual challenge of harnessing technology to enhance security systems while safeguarding sensitive data from cyber threats and privacy breaches. Futuristic e-Governance Security With Deep Learning Applications provides a timely and indispensable solution to these pressing concerns. This comprehensive book takes a global perspective, exploring the integration of intelligent systems with cybersecurity applications to protect deep learning models and ensure the secure functioning of e-governance systems.By delving into cutting-edge techniques and methodologies, this book equips scholars, researchers, and industry experts with the knowledge and tools needed to address the complex security challenges of the digital era. The authors shed light on the current state-of-the-art methods while also addressing future trends and challenges. Topics covered range from skill development and intelligence system tools to deep learning, machine learning, blockchain, IoT, and cloud computing. With its interdisciplinary approach and practical insights, this book serves as an invaluable resource for those seeking to navigate the intricate landscape of e-governance security, leveraging the power of deep learning applications to protect data and ensure the smooth operation of government systems."-- |
Beschreibung: | 19 PDFs (276 pages) Also available in print. |
Format: | Mode of access: World Wide Web. |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781668495988 |
Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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245 | 0 | 0 | |a Futuristic e-governance security with deep learning applications |c Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Madhu Sharma Gaur, Sanjeev Kumar, editors. |
264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c 2024. | |
300 | |a 19 PDFs (276 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. A study on green marketing products and green marketing practices in India -- Chapter 2. Advancements in machine learning and AI for intelligent systems in drone applications for smart city developments -- Chapter 3. Biomedical image analysis for lung cancer detection using deep learning -- Chapter 4. Cryptocurrency and bitcoin: international economy and cybersecurity -- Chapter 5. Deep learning-based soil nutrient content prediction for crop yield estimation -- Chapter 6. Enhancement of the electronic governance security infrastructure utilizing deep learning techniques -- Chapter 7. Predictive patient-centric healthcare: a novel algorithm for recommending learning applications -- Chapter 8. Reinforcement learning-driven optimization of convolutional neural networks for plant disease classification -- Chapter 9. Strategic challenges of human resources management in the industry 6.0 -- Chapter 10. Unmasking of heart disease symptoms using the COVID-19 vaccine dataset in Twitter: text feature extraction, sentiment analysis -- Chapter 11. Artificial intelligence with cloud resource allocation: cloud computing services with AI. | |
506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
520 | 3 | |a "In today's rapidly advancing digital world, governments face the dual challenge of harnessing technology to enhance security systems while safeguarding sensitive data from cyber threats and privacy breaches. Futuristic e-Governance Security With Deep Learning Applications provides a timely and indispensable solution to these pressing concerns. This comprehensive book takes a global perspective, exploring the integration of intelligent systems with cybersecurity applications to protect deep learning models and ensure the secure functioning of e-governance systems.By delving into cutting-edge techniques and methodologies, this book equips scholars, researchers, and industry experts with the knowledge and tools needed to address the complex security challenges of the digital era. The authors shed light on the current state-of-the-art methods while also addressing future trends and challenges. Topics covered range from skill development and intelligence system tools to deep learning, machine learning, blockchain, IoT, and cloud computing. With its interdisciplinary approach and practical insights, this book serves as an invaluable resource for those seeking to navigate the intricate landscape of e-governance security, leveraging the power of deep learning applications to protect data and ensure the smooth operation of government systems."-- |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 01/28/2024). | ||
650 | 0 | |a Artificial intelligence. | |
650 | 0 | |a Public administration |x Technological innovations. | |
655 | 4 | |a Electronic books. | |
700 | 1 | |a Abdul Hamid, Abu Bakar |d 1967- |e editor. | |
700 | 1 | |a Gaur, Madhu Sharma, |e editor. | |
700 | 1 | |a Kumar, Rajeev, |e editor. | |
700 | 1 | |a Kumar, Sanjeev, |e editor. | |
700 | 1 | |a Ya'akub, Noor Inayah Binti, |e editor. | |
710 | 2 | |a IGI Global, |e publisher. | |
776 | 0 | 8 | |i Print version: |z 1668495961 |z 9781668495964 |
856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-9596-4 |3 Volltext |
912 | |a ZDB-98-IGB | ||
049 | |a DE-863 |
Datensatz im Suchindex
DE-BY-FWS_katkey | ZDB-98-IGB-00319684 |
---|---|
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adam_text | |
any_adam_object | |
author2 | Abdul Hamid, Abu Bakar 1967- Gaur, Madhu Sharma Kumar, Rajeev Kumar, Sanjeev Ya'akub, Noor Inayah Binti |
author2_role | edt edt edt edt edt |
author2_variant | h a b a hab haba m s g ms msg r k rk s k sk n i b y nib niby |
author_facet | Abdul Hamid, Abu Bakar 1967- Gaur, Madhu Sharma Kumar, Rajeev Kumar, Sanjeev Ya'akub, Noor Inayah Binti |
building | Verbundindex |
bvnumber | localFWS |
callnumber-first | J - Political Science |
callnumber-label | JF1525 |
callnumber-raw | JF1525.A8 F88 2024e |
callnumber-search | JF1525.A8 F88 2024e |
callnumber-sort | JF 41525 A8 F88 42024E |
callnumber-subject | JF - Public Administration |
collection | ZDB-98-IGB |
contents | Chapter 1. A study on green marketing products and green marketing practices in India -- Chapter 2. Advancements in machine learning and AI for intelligent systems in drone applications for smart city developments -- Chapter 3. Biomedical image analysis for lung cancer detection using deep learning -- Chapter 4. Cryptocurrency and bitcoin: international economy and cybersecurity -- Chapter 5. Deep learning-based soil nutrient content prediction for crop yield estimation -- Chapter 6. Enhancement of the electronic governance security infrastructure utilizing deep learning techniques -- Chapter 7. Predictive patient-centric healthcare: a novel algorithm for recommending learning applications -- Chapter 8. Reinforcement learning-driven optimization of convolutional neural networks for plant disease classification -- Chapter 9. Strategic challenges of human resources management in the industry 6.0 -- Chapter 10. Unmasking of heart disease symptoms using the COVID-19 vaccine dataset in Twitter: text feature extraction, sentiment analysis -- Chapter 11. Artificial intelligence with cloud resource allocation: cloud computing services with AI. |
ctrlnum | (CaBNVSL)slc00005481 (OCoLC)1419198564 |
dewey-full | 352.3802854678 |
dewey-hundreds | 300 - Social sciences |
dewey-ones | 352 - General considerations of public administration |
dewey-raw | 352.3802854678 |
dewey-search | 352.3802854678 |
dewey-sort | 3352.3802854678 |
dewey-tens | 350 - Public administration and military science |
format | Electronic eBook |
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genre | Electronic books. |
genre_facet | Electronic books. |
id | ZDB-98-IGB-00319684 |
illustrated | Not Illustrated |
indexdate | 2024-11-26T14:52:00Z |
institution | BVB |
isbn | 9781668495988 |
language | English |
oclc_num | 1419198564 |
open_access_boolean | |
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physical | 19 PDFs (276 pages) Also available in print. |
psigel | ZDB-98-IGB |
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publishDateSort | 2024 |
publisher | IGI Global, |
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spelling | Futuristic e-governance security with deep learning applications Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Madhu Sharma Gaur, Sanjeev Kumar, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, 2024. 19 PDFs (276 pages) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Chapter 1. A study on green marketing products and green marketing practices in India -- Chapter 2. Advancements in machine learning and AI for intelligent systems in drone applications for smart city developments -- Chapter 3. Biomedical image analysis for lung cancer detection using deep learning -- Chapter 4. Cryptocurrency and bitcoin: international economy and cybersecurity -- Chapter 5. Deep learning-based soil nutrient content prediction for crop yield estimation -- Chapter 6. Enhancement of the electronic governance security infrastructure utilizing deep learning techniques -- Chapter 7. Predictive patient-centric healthcare: a novel algorithm for recommending learning applications -- Chapter 8. Reinforcement learning-driven optimization of convolutional neural networks for plant disease classification -- Chapter 9. Strategic challenges of human resources management in the industry 6.0 -- Chapter 10. Unmasking of heart disease symptoms using the COVID-19 vaccine dataset in Twitter: text feature extraction, sentiment analysis -- Chapter 11. Artificial intelligence with cloud resource allocation: cloud computing services with AI. Restricted to subscribers or individual electronic text purchasers. "In today's rapidly advancing digital world, governments face the dual challenge of harnessing technology to enhance security systems while safeguarding sensitive data from cyber threats and privacy breaches. Futuristic e-Governance Security With Deep Learning Applications provides a timely and indispensable solution to these pressing concerns. This comprehensive book takes a global perspective, exploring the integration of intelligent systems with cybersecurity applications to protect deep learning models and ensure the secure functioning of e-governance systems.By delving into cutting-edge techniques and methodologies, this book equips scholars, researchers, and industry experts with the knowledge and tools needed to address the complex security challenges of the digital era. The authors shed light on the current state-of-the-art methods while also addressing future trends and challenges. Topics covered range from skill development and intelligence system tools to deep learning, machine learning, blockchain, IoT, and cloud computing. With its interdisciplinary approach and practical insights, this book serves as an invaluable resource for those seeking to navigate the intricate landscape of e-governance security, leveraging the power of deep learning applications to protect data and ensure the smooth operation of government systems."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 01/28/2024). Artificial intelligence. Public administration Technological innovations. Electronic books. Abdul Hamid, Abu Bakar 1967- editor. Gaur, Madhu Sharma, editor. Kumar, Rajeev, editor. Kumar, Sanjeev, editor. Ya'akub, Noor Inayah Binti, editor. IGI Global, publisher. Print version: 1668495961 9781668495964 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-9596-4 Volltext |
spellingShingle | Futuristic e-governance security with deep learning applications Chapter 1. A study on green marketing products and green marketing practices in India -- Chapter 2. Advancements in machine learning and AI for intelligent systems in drone applications for smart city developments -- Chapter 3. Biomedical image analysis for lung cancer detection using deep learning -- Chapter 4. Cryptocurrency and bitcoin: international economy and cybersecurity -- Chapter 5. Deep learning-based soil nutrient content prediction for crop yield estimation -- Chapter 6. Enhancement of the electronic governance security infrastructure utilizing deep learning techniques -- Chapter 7. Predictive patient-centric healthcare: a novel algorithm for recommending learning applications -- Chapter 8. Reinforcement learning-driven optimization of convolutional neural networks for plant disease classification -- Chapter 9. Strategic challenges of human resources management in the industry 6.0 -- Chapter 10. Unmasking of heart disease symptoms using the COVID-19 vaccine dataset in Twitter: text feature extraction, sentiment analysis -- Chapter 11. Artificial intelligence with cloud resource allocation: cloud computing services with AI. Artificial intelligence. Public administration Technological innovations. |
title | Futuristic e-governance security with deep learning applications |
title_auth | Futuristic e-governance security with deep learning applications |
title_exact_search | Futuristic e-governance security with deep learning applications |
title_full | Futuristic e-governance security with deep learning applications Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Madhu Sharma Gaur, Sanjeev Kumar, editors. |
title_fullStr | Futuristic e-governance security with deep learning applications Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Madhu Sharma Gaur, Sanjeev Kumar, editors. |
title_full_unstemmed | Futuristic e-governance security with deep learning applications Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Madhu Sharma Gaur, Sanjeev Kumar, editors. |
title_short | Futuristic e-governance security with deep learning applications |
title_sort | futuristic e governance security with deep learning applications |
topic | Artificial intelligence. Public administration Technological innovations. |
topic_facet | Artificial intelligence. Public administration Technological innovations. Electronic books. |
url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-9596-4 |
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