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A Method of Polished Rice Image Segmentation Based on YO-LACTS for Quality Detection

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成果类型:
期刊论文
作者:
Zhou, Jinbo;Zeng, Shan;Chen, Yulong;Kang, Zhen;Li, Hao;...
通讯作者:
Shan Zeng
作者机构:
[Zhou, Jinbo; Li, Hao; Kang, Zhen; Zeng, Shan; Sheng, Zhongyin] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
[Chen, Yulong] Wuhan Polytech Univ, Coll Med & Hlth Sci, Wuhan 430023, Peoples R China.
通讯机构:
[Shan Zeng] S
School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
polished rice;RoI;YOLOv5;YOLACT
期刊:
Agriculture-Basel
ISSN:
2077-0472
年:
2023
卷:
13
期:
1
页码:
182-
基金类别:
This research was funded by Hubei province Natural Science Foundation for Distinguished Young Scholars, grant NO. 2020CFA063, and funded by excellent young and middle-aged scientific and technological innovation teams in the colleges and universities of Hubei Province, grant NO. T2021009.
机构署名:
本校为第一机构
院系归属:
数学与计算机学院
医学与健康学院
摘要:
The problem of small and multi-object polished rice image segmentation has always been one of importance and difficulty in the field of image segmentation. In the appearance quality detection of polished rice, image segmentation is a crucial part, directly affecting the results of follow-up physicochemical indicators. To avoid leak detection and inaccuracy in image segmentation qualifying polished rice, this paper proposes a new image segmentation method (YO-LACTS), combining YOLOv5 with YOLACT. We tested the YOLOv5-based object detection network, to extract Regions of Interest (RoI) from the ...

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