Deep convolutional neural networks for image-based Convolvulus sepium detection in sugar beet fields

@article{Gao2020DeepCN,
  title={Deep convolutional neural networks for image-based Convolvulus sepium detection in sugar beet fields},
  author={Junfeng Gao and Andrew P. French and Michael P. Pound and Yong He and Tony P. Pridmore and J. G. Pieters},
  journal={Plant Methods},
  year={2020},
  volume={16}
}
  • Junfeng Gao, Andrew P. French, +3 authors J. G. Pieters
  • Published in Plant Methods 2020
  • Medicine
  • Convolvulus sepium (hedge bindweed) detection in sugar beet fields remains a challenging problem due to variation in appearance of plants, illumination changes, foliage occlusions, and different growth stages under field conditions. Current approaches for weed and crop recognition, segmentation and detection rely predominantly on conventional machine-learning techniques that require a large set of hand-crafted features for modelling. These might fail to generalize over different fields and… CONTINUE READING

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