Home
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB / Edition 2
Barnes and Noble
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB / Edition 2
Current price: $145.95
Barnes and Noble
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB / Edition 2
Current price: $145.95
Size: OS
Loading Inventory...
*Product information may vary - to confirm product availability, pricing, shipping and return information please contact Barnes and Noble
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:
PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5
Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods
The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods
All 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
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.
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:
PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5
Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods
The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods
All 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
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.