Scale Space and Variational Methods in Computer Vision: 9th International Conference, SSVM 2023, Santa Margherita di Pula, Italy, May 21-25, 2023, Proceedings

This book presents the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision,SSVM 2023,which covered topics such as inverse problems, machine and deep learning, optimization, and scale space, PDEs, flow, motion, and registration.

Format: Paperback / softback
Length: 759 pages
Publication date: 02 May 2023
Publisher: Springer International Publishing AG

The 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was held in Santa Margherita di Pula, Italy, in May 2023. This conference brought together experts from around the world to discuss the latest advancements in scale space and variational methods in computer vision.

The proceedings of the conference, which included 57 papers, were meticulously reviewed and selected from a total of 72 submissions. The papers were organized into topical sections, covering various aspects of computer vision:

Inverse Problems in Imaging: This section focused on addressing challenging imaging problems, such as reconstruction, denoising, and object detection. The papers presented innovative techniques and algorithms for solving these problems.

Machine and Deep Learning in Imaging: This section explored the use of machine learning and deep learning algorithms in computer vision tasks, including image classification, object detection, and facial recognition. The papers discussed the latest developments and challenges in these areas.

Optimization for Imaging: Theory and Methods: This section covered optimization techniques for computer vision problems, such as image registration, motion estimation, and shape analysis. The papers presented novel approaches and algorithms for improving the accuracy and efficiency of these tasks.

Scale Space, PDEs, Flow, Motion, and Registration: This section dealt with scale space methods, partial differential equations (PDEs), flow models, motion analysis, and registration techniques. The papers presented advanced techniques for capturing and analyzing visual data in a variety of applications.

The conference provided a platform for researchers and practitioners to exchange ideas, share their research findings, and collaborate on future research projects. The presentations were of high quality, and the discussions were lively and informative.

Overall, the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was a successful event that contributed significantly to the advancement of computer vision research. The proceedings of the conference will be valuable for researchers, students, and practitioners in the field.

The 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was held in Santa Margherita di Pula, Italy, in May 2023. This conference brought together experts from around the world to discuss the latest advancements in scale space and variational methods in computer vision.

The proceedings of the conference, which included 57 papers, were meticulously reviewed and selected from a total of 72 submissions. The papers were organized into topical sections, covering various aspects of computer vision:

Inverse Problems in Imaging: This section focused on addressing challenging imaging problems, such as reconstruction, denoising, and object detection. The papers presented innovative techniques and algorithms for solving these problems.

Machine and Deep Learning in Imaging: This section explored the use of machine learning and deep learning algorithms in computer vision tasks, including image classification, object detection, and facial recognition. The papers discussed the latest developments and challenges in these areas.

Optimization for Imaging: Theory and Methods: This section covered optimization techniques for computer vision problems, such as image registration, motion estimation, and shape analysis. The papers presented novel approaches and algorithms for improving the accuracy and efficiency of these tasks.

Scale Space, PDEs, Flow, Motion, and Registration: This section dealt with scale space methods, partial differential equations (PDEs), flow models, motion analysis, and registration techniques. The papers presented advanced techniques for capturing and analyzing visual data in a variety of applications.

The conference provided a platform for researchers and practitioners to exchange ideas, share their research findings, and collaborate on future research projects. The presentations were of high quality, and the discussions were lively and informative.

Overall, the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was a successful event that contributed significantly to the advancement of computer vision research. The proceedings of the conference will be valuable for researchers, students, and practitioners in the field.

The 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was held in Santa Margherita di Pula, Italy, in May 2023. This conference brought together experts from around the world to discuss the latest advancements in scale space and variational methods in computer vision.

The proceedings of the conference, which included 57 papers, were meticulously reviewed and selected from a total of 72 submissions. The papers were organized into topical sections, covering various aspects of computer vision:

Inverse Problems in Imaging: This section focused on addressing challenging imaging problems, such as reconstruction, denoising, and object detection. The papers presented innovative techniques and algorithms for solving these problems.

Machine and Deep Learning in Imaging: This section explored the use of machine learning and deep learning algorithms in computer vision tasks, including image classification, object detection, and facial recognition. The papers discussed the latest developments and challenges in these areas.

Optimization for Imaging: Theory and Methods: This section covered optimization techniques for computer vision problems, such as image registration, motion estimation, and shape analysis. The papers presented novel approaches and algorithms for improving the accuracy and efficiency of these tasks.

Scale Space, PDEs, Flow, Motion, and Registration: This section dealt with scale space methods, partial differential equations (PDEs), flow models, motion analysis, and registration techniques. The papers presented advanced techniques for capturing and analyzing visual data in a variety of applications.

The conference provided a platform for researchers and practitioners to exchange ideas, share their research findings, and collaborate on future research projects. The presentations were of high quality, and the discussions were lively and informative.

Overall, the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, was a successful event that contributed significantly to the advancement of computer vision research. The proceedings of the conference will be valuable for researchers, students, and practitioners in the field.

Weight: 1169g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031319747
Edition number: 1st ed. 2023