Optical flow-based branch segmentation for complex orchard environments

@article{You2022OpticalFB,
  title={Optical flow-based branch segmentation for complex orchard environments},
  author={Alexander You and Cindy Grimm and Joseph R. Davidson},
  journal={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2022},
  pages={9180-9186}
}
Machine vision is a critical subsystem for enabling robots to be able to perform a variety of tasks in orchard environments. However, orchards are highly visually complex environments, and computer vision algorithms operating in them must be able to contend with variable lighting conditions and background noise. Past work on enabling deep learning algorithms to operate in these environments has typically required large amounts of hand-labeled data to train a deep neural network or physically… 

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