Computer Vision

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}
}

OSNet: an oriented instance segmentation network of breeding plot extraction from UAV RGB imagery

Abstract

This paper presents OSNet, an oriented instance segmentation network for breeding plot extraction from UAV RGB imagery.

Key Contributions

  • Developed an oriented instance segmentation network for breeding plot extraction
  • Achieved high accuracy in plot boundary detection from UAV RGB imagery
  • Demonstrated effectiveness for agricultural field management

Citation 

@article{zhang2025osnet,
  title={OSNet: an oriented instance segmentation network of breeding plot extraction from UAV RGB imagery},
  author={Zhang, Ruinan and Zhang, Yue and Jin, Shuai and others},
  journal={Computers and Electronics in Agriculture},
  volume={236},
  pages={110436},
  year={2025},
  publisher={Elsevier}
}

Comparison of Different Machine Learning Algorithms for the Prediction of the Wheat Grain Filling Stage Using RGB Images

Abstract

This paper presents a comparison of different machine learning algorithms for the prediction of the wheat grain filling stage using RGB images.

Citation 

@article{song2023comparison,
  title={Comparison of Different Machine Learning Algorithms for the Prediction of the Wheat Grain Filling Stage Using RGB Images},
  author={Song, Yunlin and Sun, Zhuangzhuang and Zhang, Ruinan and Min, Haijiang and Li, Qing and Cai, Jian and Wang, Xiao and Zhou, Qin and Jiang, Dong},
  journal={Plants},
  volume={12},
  number={23},
  pages={4043},
  year={2023},
  publisher={MDPI}
}

Anti-gravity stem-seeking restoration algorithm for maize seed root image phenotype detection

Abstract

This paper presents an anti-gravity stem-seeking restoration algorithm for maize seed root image phenotype detection.

Citation 

@article{mingxuan2022anti,
  title={Anti-gravity stem-seeking restoration algorithm for maize seed root image phenotype detection},
  author={Mingxuan, Zou and Wei, Lu and Hui, Luo and Ruinan, Zhang and Yiming, Deng},
  journal={Computers and Electronics in Agriculture},
  volume={202},
  pages={107337},
  year={2022},
  publisher={Elsevier}
}