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Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

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  • More about Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence


Energy efficiency is crucial for running computer vision on battery-powered systems, and the authors of this book are leading experts in the field. It offers cutting-edge solutions for real-world systems, many of which are open-sourced.

Format: Hardback
Length: 416 pages
Publication date: 23 February 2022
Publisher: Taylor & Francis Ltd


Energy efficiency is paramount for the successful operation of computer vision systems powered by batteries, such as mobile phones or drones. The authors, who are esteemed international researchers and industry professionals in this field, have compiled a comprehensive book that offers cutting-edge solutions for real-world systems, many of which are open-sourced.

The importance of energy efficiency in computer vision cannot be overstated. As the demand for mobile devices and drones continues to grow, the need for efficient energy consumption becomes increasingly crucial. Traditional computer vision systems, which rely on powerful processors and graphics cards, consume a significant amount of power, which can quickly drain batteries and limit the operational duration of these devices.

The authors of this book have recognized the challenges posed by energy efficiency and have developed innovative solutions to address them. They have leveraged their extensive expertise in the field to provide practical insights and techniques that can be applied to real-world systems. The book covers a wide range of topics, including energy-efficient image processing algorithms, power management strategies, and hardware design considerations.

One of the key strengths of this book is its focus on practical solutions. The authors have collaborated with industry partners to develop and test their algorithms on real-world systems, ensuring that the solutions presented are both effective and scalable. They have also provided open-source code and documentation, allowing others to build upon and improve their work.

In addition to its technical content, the book also offers valuable insights into the business and economic aspects of energy-efficient computer vision. The authors discuss the potential benefits of energy-efficient systems, such as reduced operating costs, increased battery life, and reduced environmental impact. They also explore the challenges and barriers to implementing energy-efficient solutions, such as the need for standardized interfaces, the lack of industry standards, and the high cost of energy-efficient hardware.

Overall, this book is a valuable resource for anyone interested in energy-efficient computer vision. It provides a comprehensive overview of the field, covering both technical and practical aspects, and offers cutting-edge solutions for real-world systems. Whether you are a researcher, engineer, or industry professional, this book will help you develop the skills and knowledge necessary to build energy-efficient and sustainable computer vision systems.

Weight: 828g
Dimension: 160 x 241 x 28 (mm)
ISBN-13: 9780367744700

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