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Li, H., Kong, M. and Shi, Y. (2024) Tea Bud Detection Model in a Real Picking Environment Based on an Improved Yolov5. Biomimetics, 9, Article 692.
https://doi.org/10.3390/biomimetics9110692

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.