SenNet: A dual-branch image semantic segmentation network for wheat senescence evaluation and high-yielding variety screening
Abstract
This paper presents SenNet, a dual-branch image semantic segmentation network for wheat senescence evaluation and high-yielding variety screening.
Citation
@article{yao2025sennet,
title={SenNet: A dual-branch image semantic segmentation network for wheat senescence evaluation and high-yielding variety screening},
author={Yao, Jiaqi and Jin, Shichao and Zang, Jingrong and Zhang, Ruinan and Wang, Yu and Su, Yanjun and Guo, Qinghua and Ding, Yanfeng and Jiang, Dong},
journal={Computers and Electronics in Agriculture},
volume={237},
pages={110632},
year={2025},
publisher={Elsevier}
}
- Posted on:
- June 2, 2025
- Length:
- 1 minute read, 72 words
- See Also:
- PhenoSR: Enhancing organ-level phenotyping with super-resolution RGB UAV imagery for large-scale field experiments
- 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