• DOI:10.1016/j.compag.2020.105952
Corpus ID: 222341937

Semantic Segmentation for Partially Occluded Apple Trees Based on Deep Learning

@article{Chen2021SemanticSF,
  title={Semantic Segmentation for Partially Occluded Apple Trees Based on Deep Learning},
  author={Z. Chen and D. Ting and Rhys Newbury and C. Chen},
  journal={Comput. Electron. Agric.},
  year={2021},
  volume={181},
  pages={105952}
}

Z. Chen, D. Ting, +1 author C. Chen

Published 2021

Computer Science

Comput. Electron. Agric.

Fruit tree pruning and fruit thinning require a powerful vision system that can provide high resolution segmentation of the fruit trees and their branches. However, recent works only consider the dormant season, where there are minimal occlusions on the branches or fit a polynomial curve to reconstruct branch shape and hence, losing information about branch thickness. In this work, we apply two state-of-the-art supervised learning models U-Net and DeepLabv3, and a conditional Generative… CONTINUE READING

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