Computer vision [2nd ed.] : algorithms and applications
By: Szeliski, Richard.
Series: Texts in computer science. / edited by David Gries and Orit Hazzan.Publisher: Switzerland Springer Nature 2022Edition: 2nd ed.Description: xxii, 925p.ISBN: 9783030343712.Subject(s): Computer vision | Image processing | Image processing -- MathematicsDDC classification: 006.37 | Sz25c2 Summary: 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.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books
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PK Kelkar Library, IIT Kanpur | General Stacks | 006.37 Sz25c2 (Browse shelf) | Checked out to ADITYA SHARMA (S20005400) | 15/05/2024 | A185871 |
Total holds: 0
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: General Stacks Close shelf browser
| 006.37 N654f4 Feature extraction and image processing for computer vision [4th ed.] | 006.37 P395c Computer vision | 006.37 Sz25c Computer vision | 006.37 Sz25c2 Computer vision [2nd ed.] | 006.3843 Am68u Universal quantum computing | 006.3843 B456q Quantum computing for everyone | 006.4 An14g A guide for machine vision in quality control |
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.
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