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SY-Net: A Rice Seed Instance Segmentation Method Based on a Six-Layer Feature Fusion Network and a Parallel Prediction Head Structure

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成果类型:
期刊论文
作者:
Ye, Sheng;Liu, Weihua;Zeng, Shan;Wu, Guiju;Chen, Liangyan;...
通讯作者:
Liu, WH
作者机构:
[Chen, Liangyan; Ye, Sheng; Liu, Weihua; Yan, Zi; Lai, Huaqing] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
[Zeng, Shan] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
[Wu, Guiju] China Earthquake Adm, Inst Seismol, Key Lab Earthquake Geodesy, Wuhan 430023, Peoples R China.
通讯机构:
[Liu, WH ] W
Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
instance segmentation;deep learning;rice seed;small target;feature fusion
期刊:
Sensors
ISSN:
1424-3210
年:
2023
卷:
23
期:
13
页码:
6194-
基金类别:
This work was supported by Excellent Young and Middle-aged Scientific and Technological Innovation Teams at the Colleges and Universities of Hubei province project under grant No. T2021009.
机构署名:
本校为第一且通讯机构
院系归属:
电气与电子工程学院
数学与计算机学院
摘要:
During the rice quality testing process, the precise segmentation and extraction of grain pixels is a key technique for accurately determining the quality of each seed. Due to the similar physical characteristics, small particles and dense distributions of rice seeds, properly analysing rice is a difficult problem in the field of target segmentation. In this paper, a network called SY-net, which consists of a feature extractor module, a feature pyramid fusion module, a prediction head module and a prototype mask generation module, is proposed for rice seed instance segmentation. In the feature...

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