Building Intelligent Systems

Utilizing Computer Vision, Data Mining, and Machine Learning
Book Type: Intel Press Books
Category: Programming

Consumers are now demanding and expecting more from technology. Building intelligence into our devices is a promising way to satisfy this demand by providing more personalized experiences. In Building Intelligent Systems the authors investigate how computer vision, machine learning, and data mining can be used together to build smarter devices and systems. Additionally, they explore some of the practical considerations of using artificial intelligence in the real world, tackling issues that are often overlooked in academic circles, such as performance optimization, benchmarking, robustness, and privacy.

Face recognition and motion detection will be game changers. This book is one of a kind and goes into great technical details in explaining various methodologies and their practical applications.

Sule Balkan, PhD Clinical Associate Professor Arizona State University W.P. Carey School of Business Department of Information Systems

Intelligent systems built on existing research results can solve some real problems and benefit our life. This book shows us how to create these systems

Qingjie Zhao Professor Beijing Institute of Technology

This is a comprehensive textbook for those entering the field and an excellent reference for those of us who are working in the field. It will have a prominent place in my library where I can readily reach it.

Kenneth Salsman Director, New Technology Aptina, LLC

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About the Author(s)

Phil Tian

Phil Tian is an enterprise architect in the IT Labs at Intel. He holds a PhD in Computer Science from Tsinghua University and got his Automation Master’s degree and BCS degree from North China Electric Power University.

His research interests include machine learning, data mining, business intelligence, predictive analytics, and big data. He is driving a business intelligence community in China. Prior to joining Intel, Dr. Tian was an associate professor at Beijing Jiaotong University and a visiting professor at the University of Illinois at Urbana-Champaign. He has authored a couple of books and numerous of research papers.

Sanjay Addicam

Sanjay Addicam is an Intel staff software engineer with a focus on video analytics, machine learning, and data mining algorithms.  He has a Masters in Information Sciences from the University of Maryland. His primary interest is in developing a privacy-friendly targeted advertising framework for digital signs. This work has been featured in SigKDD 2012.

Shahzad Malik

Shahzad Malik is a senior software architect in the Intelligent Systems Group at Intel. He holds a PhD in Computer Science from the University of Toronto, and the MCS and BCS degrees from Carleton University.

Prior to joining Intel, he was co-founder and CTO of CognoVision Solutions, an audience measurement and retail intelligence company that developed real-time computer vision systems including face detection and people tracking modules. Intel subsequently acquired CognoVision in 2010. In addition to a background in computer vision, Dr. Malik has authored papers in the areas of computer graphics, augmented reality, and human-computer interaction.