My Account Log in

1 option

Scale Space and Variational Methods in Computer Vision : 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019, Proceedings / edited by Jan Lellmann, Martin Burger, Jan Modersitzki.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Contributor:
Lellmann, Jan, Editor.
Burger, Martin, Editor.
Modersitzki, Jan, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11603
Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11603
Language:
English
Subjects (All):
Computer vision.
Numerical analysis.
Computer science-Mathematics.
Artificial intelligence.
Computer Vision.
Numerical Analysis.
Mathematical Applications in Computer Science.
Artificial Intelligence.
Local Subjects:
Computer Vision.
Numerical Analysis.
Mathematical Applications in Computer Science.
Artificial Intelligence.
Physical Description:
1 online resource (XVII, 574 pages) : 302 illustrations, 153 illustrations in color.
Edition:
1st ed. 2019.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. The 44 papers included in this volume were carefully reviewed and selected for inclusion in this book. They were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction; scale-space methods; segmentation and labeling; and variational methods. .
Other Format:
Printed edition:
ISBN:
978-3-030-22368-7
9783030223687
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account