Название: AI and Deep Learning Enabled Surveillance System Using Image ProcessingАвтор: Jay Kumar Pandey, Mritunjay Rai, Faizan Ahmad
Издательство: Emerald Publishing Limited
Год: 2026
Страниц: 289
Язык: английский
Формат: pdf (true), epub
Размер: 32.6 MB
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.
Machine Learning (ML) and Deep Learning (DL) have been leveraged in surveillance systems to change the way of threat identification, criminal prevention, and public safety monitoring. In this chapter, we give an overview of related Machine Learning and DL techniques, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and transformer‐based architectures, as well as the use of them to solve problems in image and video surveillance. Then it looks at how precise these models can make item identification, facial recognition, and activity recognition. Real‐time inference in surveillance applications is also covered in the chapter, as well as the training datasets and the model optimization strategies. Also, it looks into the issue of computing cost, data privacy, and the ethics of AI‐powered monitoring. It presents here extensively the impact of ML and DL algorithms in bringing forth forthcoming generations of intelligent security 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.
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