Training networks without wavefront label for pixel-based wavefront sensing
Traditional image-based wavefront sensing often faces challenges in efficiency and stagnation. Deep learning methods, when properly trained, offer superior robustness and performance. However, obtaining sufficient real labeled data remains a significant challenge. Existing self-supervised methods ba...
Saved in:
| Main Authors: | Yuxuan Liu, Xiaoquan Bai, Boqian Xu, Chunyue Zhang, Yan Gao, Shuyan Xu, Guohao Ju |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-03-01
|
| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2025.1537756/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Single-Shot Wavefront Sensing in Focal Plane Imaging Using Transformer Networks
by: Hangning Kou, et al.
Published: (2025-03-01) -
Fiber-Connected Wavefront-Sensing System for Large Segmented Space Telescopes
by: Qi-Chang An, et al.
Published: (2023-01-01) -
Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach
by: Yangchen Wang, et al.
Published: (2025-03-01) -
Design considerations for wavefront sensing with self-referencing interferometers in adaptive optics systems
by: MacGillivray Alexander C., et al.
Published: (2025-01-01) -
Modern approaches to cataract surgery based on wavefront analysis
by: E.M. Titarenko, et al.
Published: (2023-03-01)