AI and Deep Learning Enabled Surveillance System Using Image Processing is an essential resource for anyone interested in the convergence of advanced technologies to enhance surveillance capabilities. This book explores in detail how artificial intelligence and deep learning can be applied to image processing, offering a transformative approach to modern surveillance systems. It covers foundational concepts of AI and deep learning, explaining how these technologies are reshaping the way we understand and utilize image data. The book emphasizes practical implementation, guiding readers through the integration of AI algorithms with image processing techniques to create sophisticated, real-time surveillance solutions.
Through in-depth discussions and real-world case studies, the book highlights the applications of AI in various surveillance contexts, such as public safety, traffic monitoring, and access control. Readers will learn about the latest advancements in neural networks, object detection, and anomaly detection, gaining insights into developing and deploying intelligent surveillance systems. Additionally, the book addresses critical ethical and privacy considerations, ensuring that readers are aware of the balance between enhanced security and individual privacy rights. This comprehensive guide is an invaluable tool for professionals and researchers aiming to harness the power of AI and deep learning in the field of surveillance.
AI and Deep Learning Enabled Surveillance System Using Image Processing is an essential resource for anyone interested in the convergence of advanced technologies to enhance surveillance capabilities.
Chapter
1. Integrating Image Processing and AI in Modern Surveillance: A
Roadmap for Smart Cities; Vaibhav Sharma, Akshay Raj, and Zeba Rani
Chapter
2. Revolutionizing Modern Surveillance Systems: Harnessing the Power
of Neural Networks for Advanced Video Analytics, Real-Time Object Detection,
and Predictive Security Applications; Lokesh Jain and Nitin Saraswat
Chapter
3. Machine Learning and Deep Learning Algorithms in Surveillance
Systems; Nitendra Kumar, Sandeep Mathur, and Ramit Sehgal
Chapter
4. Understanding Neural Networks in Surveillance Systems; Sandeep
Mathur, Ramit Sehgal, and Nitendra Kumar
Chapter
5. Integration of Thermal Imaging and AI for Night-Time Surveillance;
Laxman Singh, Sonia Arora, Manali Gupta, and Mritunjay Rai
Chapter
6. Enhancing Real-Time Surveillance Video Analysis with AI-Powered
Deep Learning Techniques; Shivani Shingh and Jay Kumar Pandey
Chapter
7. AirNet X: Object Detection from Aerial Images for Enhanced
Disaster Detection; Syed Rafiammal, M. Padma Usha, SyedaZainab, Jiyaad Ahmed,
and Najumudeen
Chapter
8. Use of Remote Sensing for Precision Agriculture: Areas of Research
and Prospects; Karim Ennouri, Mohamed Ali Triki, and Monia Ennouri
Chapter
9. Robust Object Detection for Autonomous Vehicles on Indian Roads
Using YOLOv8; Priyanshu Nawal and Pawan Singh
Chapter
10. Intelligent Surveillance: Enhancing Security Through Automation
and AI; Poonam Yadav and Prashant Kumar
Jay Kumar Pandey is currently an Assistant Professor in the Department of Electrical and Electronics Engineering at Shri Ramswaroop Memorial University, Barabanki, U.P, India.
Mritunjay Rai is currently an Assistant Professor in the Department of Electrical and Electronics Engineering at Shri Ramswaroop Memorial University, Barabanki, U.P, India.
Faizan Ahmad is a Lecturer in Computer Science and/or Games Development at Cardiff School of Technologies, Cardiff Metropolitan University, UK.
