Scale Space and Variational Methods in Computer Vision : 8th International Conference, SSVM 2021, Virtual Event, May 16¿20, 2021, Proceedings

Abderrahim Elmoataz

ISBN 10: 3030755487 / ISBN 13: 9783030755485

Published by Springer International Publishing, 2021

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 8th International Conference onScale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic.The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging.

Seller Inventory # 9783030755485

Bibliographic Details

• Title: Scale Space and Variational Methods in Computer Vision : 8th International Conference, SSVM 2021, Virtual Event, May 16¿20, 2021, Proceedings
• Publisher: Springer International Publishing
• Publication Date: 2021
• Language: English
• ISBN 10: 3030755487
• ISBN 13: 9783030755485
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This book constitutes the proceedings of the 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic.

The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging.