Tea chrysanthemum detection under unstructured environments using the TC-YOLO model

作者：

Highlights：

• TC-YOLO was designed for tea chrysanthemum detection in a field environment.

• TC-YOLO shows supreme performance compared to other CNN detection architectures.

• The effects of environmental variations for detection accuracy were quantified.

• TC-YOLO has the potential to be deployed in a tea chrysanthemum picking robot.

摘要

•TC-YOLO was designed for tea chrysanthemum detection in a field environment.•TC-YOLO shows supreme performance compared to other CNN detection architectures.•The effects of environmental variations for detection accuracy were quantified.•TC-YOLO has the potential to be deployed in a tea chrysanthemum picking robot.

论文关键词：Tea chrysanthemum,Flowering stage detection,Deep convolutional neural network,Agricultural robotics

论文评审过程：Received 29 August 2021, Revised 1 December 2021, Accepted 26 December 2021, Available online 31 December 2021, Version of Record 4 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116473