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AI and Deep Learning Enabled Surveillance System Using Image Processing

Edited by:
Jay Kumar Pandey, Shri Ramswaroop Memorial University
Mritunjay Rai, Shri Ramswaroop Memorial University
Faizan Ahmad, Cardiff School of Technologies

Call For Papers

BOOK DESCRIPTION:
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 provides a detailed exploration of 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.

TOPICS OF INTEREST:
Introduction to Overview of AI in Surveillance System

Evolution from Traditional to Intelligent Surveillance Systems

Fundamentals of Artificial Intelligence and Deep Learning

Basic Concepts of AI & Introduction to Machine Learning and Deep Learning Key Algorithms and Techniques in AI

Basics of Image Processing & Digital Image Processing: An Overview

Key Techniques: Filtering, Segmentation, and Enhancement to Image Processing Tools and Libraries

Deep Learning for Image Recognition to Understanding Neural Networks

Convolutional Neural Networks (CNNs) and Training and Fine-tuning Deep Learning Models

Integration of AI and Image Processing in Surveillance Systems & Designing AI Enabled Surveillance Systems

Hardware and Software Requirements for Frameworks and Development Tools

Real Time Image and Video Analysis Techniques for Real-time Processing

Object Detection and Tracking Behavioral Analysis and Anomaly Detection

Applications in Surveillance in Public Safety and Law Enforcement

Traffic Monitoring and Management to Access Control and Security in Private Properties

Case Studies: Implementation in Urban Surveillance and AI in Retail Security Success Stories and Lessons Learned

Ethical and Privacy Considerations: Balancing Security and Privacy and Ethical Implications of AI Surveillance

Regulatory Frameworks and Compliance

PROPOSAL INFORMATION:
Proposals should be made on one single-spaced page, and consist of your name and affiliation, email address, a tentative title, and an abstract (200-250 words). Please include an additional page with a brief biography (200-300 words) and relevant professional publications. All proposals should be sent as a single Word file of 2 pages to Jay Kumar Pandey (editedresearchworks@gmail.com) by November 25, 2024.

CHAPTER SUBMISSION INFORMATION:
Authors of accepted proposals will be notified by November 25, 2024 about the status of their submission and sent chapter guidelines. Full chapters, ranging from 7,000 to 8,000 words in Times New Roman 12, double spaced text, inclusive of title, abstract, manuscript, and references, should be submitted as a Microsoft Word email attachment by November 30, 2024. Manuscripts should conform to 6th edition APA style conventions. See Author Guidelines. Graphics and images may be included.

Chapters should draw from the author/s own research and include case studies and reflective questions for readers to engage in and think actively about concepts and processes. Central themes should be explained in text boxes to engage the reader in the arguments presented. The end of the chapter should provide a summary of key reflections and insights on the research methodology, and recommendations for further reading may provide a wide range of current sources for further exploration and encourage readers to expand their knowledge.

SCHEDULE FOR PUBLICATION:
Abstract Submission: November 25, 2024
Notification of Invite to Submit Chapter: November 30, 2024
Submission of Book Chapter: December 30, 2024
Reviews of Book Chapter Manuscripts Sent to Author(s): January 30, 2025
Receipt by Editors of Final Draft of Book Chapters: March 30, 2025
Final Book Submitted to Publisher: April 30, 2025
Anticipated Publication: Spring 2025

Send all inquiries to Jay Kumar Pandey at: editedresearchworks@gmail.com

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