Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation

@article{Albert2022UnsupervisedDA,
  title={Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation},
  author={Paul Albert and Mohamed Saadeldin and Badri Narayanan and Jaime B. Fernandez and Brian Mac Namee and Deirdre Hennessey and Noel E. O'Connor and Kevin McGuinness},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2022},
  pages={1635-1645}
}
Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms… 

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