Computer Vision : Algorithms and Applications
Szeliski, Richard
ISBN 10: 3030343715 ISBN 13: 9783030343712
Published by Springer, 2022
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Synopsis:
Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.
More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.
Topics and features:
- Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses
- Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality
- Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
- Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade
- Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
About the Author:
Dr. Richard Szeliski has more than 40 years’ experience in computer vision research, most recently at Facebook and Microsoft Research, where he led the Computational Photography and Interactive Visual Media groups. He is currently an Affiliate Professor at the University of Washington where he co-developed (with Steve Seitz) the widely adopted computer vision curriculum on which this book is based. He was awarded the IEEE Computer Society PAMI Distinguished Researcher Award in 2017 and is an IEEE and ACM Fellow.
"About this title" may belong to another edition of this title.
Bibliographic Details
Title: Computer Vision : Algorithms and Applications
Publisher: Springer
Publication Date: 2022
Binding: Hardcover
Condition: New
Edition: 2nd Edition
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Computer Vision: Algorithms and Applications (Texts in Computer Science)
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ISBN 10: 3030343715
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Computer Vision
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ISBN 10: 3030343715
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Truly comprehensive computer vision textbookHighly anticipated new edition updated with the latest state-of-the-art techniques, and featuring new material on machine learning, deep learning, and deep neural networksStructu. Seller Inventory # 458542200
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Computer Vision: Algorithms and Applications
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Buch. Condition: Neu. Computer Vision | Algorithms and Applications | Richard Szeliski | Buch | XXII | Englisch | 2022 | Springer | EAN 9783030343712 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 117500454
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Computer Vision (Hardcover)
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Hardcover. Condition: new. Hardcover. Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projectsIncludes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decadeProvides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and softwareSuitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision. supplies supplementary course material for students at an associated website.Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783030343712
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Computer Vision: Algorithms and Applications (Texts in Computer Science)
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