Remote Sensing

PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification

Abstract

This paper presents PhenoNet, a two-stage lightweight deep learning framework for real-time wheat phenophase classification using remote sensing imagery.

Key Contributions

  • Developed a lightweight deep learning architecture for real-time processing
  • Achieved high accuracy in wheat phenophase classification
  • Demonstrated practical applicability for agricultural monitoring

Citation 

@article{zhang2024phenonet,
  title={PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification},
  author={Zhang, Ruinan and Jin, Shuai and Zhang, Yue and others},
  journal={ISPRS Journal of Photogrammetry and Remote Sensing},
  volume={208},
  pages={136--157},
  year={2024},
  publisher={Elsevier}
}

Enhancing wheat crop physiology monitoring through spectroscopic analysis of stomatal conductance dynamics

Abstract

This paper presents a spectroscopic analysis approach for enhancing wheat crop physiology monitoring through stomatal conductance dynamics.

Citation 

@article{cheng2024enhancing,
  title={Enhancing wheat crop physiology monitoring through spectroscopic analysis of stomatal conductance dynamics},
  author={Cheng, KH and Sun, Zhuangzhuang and Zhong, Wanlu and Wang, Zhihui and Visser, Marco and Liu, Shuwen and Yan, Zhengbing and Zhao, Yingyi and Zhang, Ruinan and Zang, Jingrong and others},
  journal={Remote Sensing of Environment},
  volume={312},
  pages={114325},
  year={2024},
  publisher={Elsevier}
}

Simultaneous prediction of wheat yield and grain protein content using multitask deep learning from time-series proximal sensing

Abstract

This paper presents a multitask deep learning approach for simultaneous prediction of wheat yield and grain protein content using time-series proximal sensing data.

Citation 

@article{sun2022simultaneous,
  title={Simultaneous prediction of wheat yield and grain protein content using multitask deep learning from time-series proximal sensing},
  author={Sun, Zhuangzhuang and Li, Qing and Jin, Shichao and Song, Yunlin and Xu, Shan and Wang, Xiao and Cai, Jian and Zhou, Qin and Ge, Yan and Zhang, Ruinan and others},
  journal={Plant Phenomics},
  year={2022},
  publisher={AAAS}
}