Impurity/Breakage Assessment of Vehicle-Mounted Dynamic Rice Grain Flow on Combine Harvester Based on Improved Deeplabv3+ and YOLOv4

Impurity/Breakage Assessment of Vehicle-Mounted Dynamic Rice Grain Flow on Combine Harvester Based on Improved Deeplabv3+ and YOLOv4

It is difficult to extract small and dense objects with random state, such as grain and impurity, in image of vehicle-mounted dynamic rice grain flow on combine harvester. Therefore, this paper improves Deeplabv3+ by constructing MobileNetv2 in coding layer and adding ECA(Efficient Channe...

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Bibliographic Details
Main Authors: Qian Zhang, Jinpeng Hu, Lizhang Xu, Qibing Cai, Xun Yu, Peng Liu
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Breakage rate
grain flow
impurity rate
rice harvest
vehicle vision
Online Access:https://ieeexplore.ieee.org/document/10124771/

Internet

https://ieeexplore.ieee.org/document/10124771/

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