PhenoSR: Enhancing organ-level phenotyping with super-resolution RGB UAV imagery for large-scale field experiments
Abstract
This paper presents PhenoSR, a method for enhancing organ-level phenotyping with super-resolution RGB UAV imagery for large-scale field experiments.
Key Contributions
- Developed super-resolution techniques for RGB UAV imagery
- Enhanced organ-level phenotyping capabilities
- Demonstrated effectiveness for large-scale field experiments
Citation
@article{zhang2025phenosr,
title={PhenoSR: Enhancing organ-level phenotyping with super-resolution RGB UAV imagery for large-scale field experiments},
author={Zhang, Ruinan and Jin, Shuai and Wang, Yue and others},
journal={ISPRS Journal of Photogrammetry and Remote Sensing},
volume={228},
pages={582--602},
year={2025},
publisher={Elsevier}
}
- Posted on:
- July 14, 2025
- Length:
- 1 minute read, 76 words
- See Also:
- SenNet: A dual-branch image semantic segmentation network for wheat senescence evaluation and high-yielding variety screening
- OSNet: an oriented instance segmentation network of breeding plot extraction from UAV RGB imagery
- PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification