Tracking and Counting of Tomato at Different Growth Period Using an Improving YOLO-Deepsort Network for Inspection Robot

Tracking and Counting of Tomato at Different Growth Period Using an Improving YOLO-Deepsort Network for Inspection Robot

To realize tomato growth period monitoring and yield prediction of tomato cultivation, our study proposes a visual object tracking network called YOLO-deepsort to identify and count tomatoes in different growth periods. Based on the YOLOv5s model, our model uses shufflenetv2, combined with the CBAM...

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Bibliographic Details
Main Authors: Yuhao Ge, Sen Lin, Yunhe Zhang, Zuolin Li, Hongtai Cheng, Jing Dong, Shanshan Shao, Jin Zhang, Xiangyu Qi, Zedong Wu
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Machines
Subjects:
facility agriculture
deep learning
lightweight optimization
yield forecast
object tracking
tomato
Online Access:https://www.mdpi.com/2075-1702/10/6/489

Internet

https://www.mdpi.com/2075-1702/10/6/489

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