Wei Qi Yan Livres

Focusing on the integration of deep learning, machine learning, and artificial neural networks, this textbook offers a progressive approach to understanding machine intelligence. It emphasizes knowledge transfer while incorporating graphical theory, mathematical models, and algorithmic implementation. Additionally, the book covers essential topics such as dataset preparation, programming, and the analysis and evaluation of results, making it a comprehensive resource for those looking to deepen their understanding of these advanced technologies.

This concise textbook examines the fundamental aspects of intelligent computing for surveillance systems, from camera calibration and data capturing, to secure data transmission. The text covers digital surveillance from the level of an individual object or biometric feature, to the full lifecycle of an event. This is followed by a detailed discussion on how an intelligent system can independently monitor and learn from an event, and invite human input when necessary. The book concludes with a presentation on how the system can be enhanced through the use of supercomputing technology. Features: contains exercises at the end of every chapter, and a glossary; covers the key issues of computer network infrastructure, security, monitoring and forensics, and the essential aspects of object analysis; reviews algorithms for surveillance data analytics using biometric features; discusses the use of AI for surveillance events; reviews algorithms that trigger an alarm to alert a member of security staff.