Advanced Techniques for Anomaly Detection
Beyond the Basics
Seiten
2025
CRC Press (Verlag)
978-1-032-72930-5 (ISBN)
CRC Press (Verlag)
978-1-032-72930-5 (ISBN)
The book will also summarize various protocols that work based on learning strategies and applied intelligence in the context of IoT environments.
This book is a comprehensive guide that explores the latest developments in anomaly detection techniques across a range of fields, including cybersecurity, finance, image processing, sensor networks, social network analysis, health systems, and IoT systems. With 6 chapters covering various topics such as deep learning-based anomaly detection, feature selection and extraction techniques, ensemble methods, and evaluation metrics, this book offers a comprehensive understanding of advanced anomaly detection techniques and their applications in different fields. This book will be an excellent resource for researchers, practitioners, and students interested in anomaly detection and its applications in various domains.
This book is a comprehensive guide that explores the latest developments in anomaly detection techniques across a range of fields, including cybersecurity, finance, image processing, sensor networks, social network analysis, health systems, and IoT systems. With 6 chapters covering various topics such as deep learning-based anomaly detection, feature selection and extraction techniques, ensemble methods, and evaluation metrics, this book offers a comprehensive understanding of advanced anomaly detection techniques and their applications in different fields. This book will be an excellent resource for researchers, practitioners, and students interested in anomaly detection and its applications in various domains.
Abdul Wahid, PhD, Department of Computer Science and Engineering, Indian Institute of Information Technology, Dharwad, India. Praveen Kumar Donta, PhD, Department of Computer and Systems Sciences, Stockholm, Sweden.
Chapter 1 : Anomaly Detection in Carbon Sequestration: Advancements, Challenges, and Future Directions. Chapter 2: Intelligent Anomaly Detection in Social Media. Chapter 3: Anomaly Detection in Health-Care. Chapter 4: Safeguarding Health in the Cloud: A Cutting-Edge Machine Learning Intrusion Detection. Chapter 5: Deep Learning for Anomaly Detection in IoT Time Series. Chapter 6: Pen Ink Analysis in Handwritten Document Forensics: Classification and Current Trends
| Erscheinungsdatum | 12.04.2025 |
|---|---|
| Zusatzinfo | 5 Tables, black and white; 42 Line drawings, black and white; 42 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 520 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-032-72930-9 / 1032729309 |
| ISBN-13 | 978-1-032-72930-5 / 9781032729305 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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