Prediction of Feed Quantity for Wheat Combine Harvester Based on Improved YOLOv5s and Weight of Single Wheat Plant without Stubble

Prediction of Feed Quantity for Wheat Combine Harvester Based on Improved YOLOv5s and Weight of Single Wheat Plant without Stubble

In complex field environments, wheat grows densely with overlapping organs and different plant weights. It is difficult to accurately predict feed quantity for wheat combine harvester using the existing YOLOv5s and uniform weight of a single wheat plant in a whole field. This paper proposes a feed q...

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Bibliographic Details
Main Authors: Qian Zhang, Qingshan Chen, Wenjie Xu, Lizhang Xu, En Lu
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Agriculture
Subjects:
feed quantity prediction
wheat combine harvester
neural network
vehicle vision
height estimation
Online Access:https://www.mdpi.com/2077-0472/14/8/1251

Internet

https://www.mdpi.com/2077-0472/14/8/1251

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