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...
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| Other Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2024.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "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."-- |
| Physical Description: | 19 PDFs (276 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781668495988 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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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. | |
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| 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. | |
| 653 | |a Artificial Intelligence. | ||
| 653 | |a Blockchain Applications. | ||
| 653 | |a Cloud Computing. | ||
| 653 | |a Cybersecurity. | ||
| 653 | |a Data Ethics. | ||
| 653 | |a Deep Learning. | ||
| 653 | |a Digital Era. | ||
| 653 | |a E-Governance. | ||
| 653 | |a Intelligence System. | ||
| 653 | |a Internet of Things (IoT). | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Privacy Concerns. | ||
| 653 | |a Security Breaches. | ||
| 653 | |a State-Of-The-Art Methods. | ||
| 653 | |a Technology Integration. | ||
| 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. | |
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| 912 | |a ZDB-98-IGB | ||
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|---|---|
| _version_ | 1826942602564337664 |
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| author2 | Abdul Hamid, Abu Bakar 1967- Gaur, Madhu Sharma Kumar, Rajeev Kumar, Sanjeev Ya'akub, Noor Inayah Binti |
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| author_facet | Abdul Hamid, Abu Bakar 1967- Gaur, Madhu Sharma Kumar, Rajeev Kumar, Sanjeev Ya'akub, Noor Inayah Binti |
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| 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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| 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 Seiten) 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. Artificial Intelligence. Blockchain Applications. Cloud Computing. Cybersecurity. Data Ethics. Deep Learning. Digital Era. E-Governance. Intelligence System. Internet of Things (IoT). Machine Learning. Privacy Concerns. Security Breaches. State-Of-The-Art Methods. Technology Integration. 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 |
| 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. |
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