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A practical introduction to intelligent computer vision theory, design, implementation, and technology
The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods―especially among adaboost varieties and particle filtering methods―have made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including:
A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website.
About the Author:
Professor Bangjun Lei, Dr. Guangzhu Xu, and Dr. Ming Feng are with The Institute of Intelligent Vision and Image Information, China Three Gorges University, China.
Professor Yaobin Zou is an associate professor at China Three Gorges University.
Dr. Ferdinand van der Heijden, Ph.D., is on the faculty of theDepartment of Signals and Systems, University of Twente, Netherlands.
Professor Dick de Ridder is Professor at the Bioinformatics lab at Wageningen University, Netherlands.
Professor David M. J. Tax, is a researcher with the Pattern Recognition laboratory, Delft University of Technology.
Title: Classification, Parameter Estimation and ...
Publisher: Wiley
Publication Date: 2017
Binding: Hardcover
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Edition: 2nd Edition
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Hardcover. Condition: new. Hardcover. A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methodsespecially among adaboost varieties and particle filtering methodshave made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including: PRTools5 software for MATLABespecially the latest representation and generalization software toolbox for PRTools5Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methodsThe latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methodsAll new coverage of the Adaboost and its implementation in PRTools5. A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website. A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781119152439
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Hardcover. Condition: new. Hardcover. A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methodsespecially among adaboost varieties and particle filtering methodshave made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including: PRTools5 software for MATLABespecially the latest representation and generalization software toolbox for PRTools5Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methodsThe latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methodsAll new coverage of the Adaboost and its implementation in PRTools5. A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website. A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781119152439
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