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Pan, Z., Gu, J., Wang, W., Fang, X., Xia, Z., Wang, Q., et al. (2024) Picking Point Identification and Localization Method Based on Swin-Transformer for High-Quality Tea. Journal of King Saud University—Computer and Information Sciences, 36, Article ID: 102262.
https://doi.org/10.1016/j.jksuci.2024.102262

has been cited by the following article:

• TITLE: Tea Image Recognition and Research on Structure of Tea Picking End-Effector

  AUTHORS: Biao Huang, Shiping Zou

  KEYWORDS: Image Recognition of Tea Leaves, Tea Picking End-Effector, Tea PickingStructure Design

  JOURNAL NAME: Journal of Electronics Cooling and Thermal Control, Vol.13 No.3, September 30, 2024

  ABSTRACT: The automated picking technology of tea is an important part of the development of smart agriculture, which affects the development of the tea industry to a certain extent. Tea leaf recognition and robotic tea picking end-effector are the key technologies for automated tea picking. This paper proposes a set of algorithms for tea leaf differentiation and recognition based on the principle of colour difference. And on the basis of this algorithm, a tea picking end-effector is designed. The experiments show that the designed tea picking end-effector has good recognition ability and high tea picking speed.