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An Improved Encoder-Decoder Network Based on Strip Pool Method Applied to Segmentation of Farmland Vacancy Field

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成果类型:
期刊论文
作者:
Zhang, Xixin;Yang, Yuhang;Li, Zhiyong;Ning, Xin;Qin, Yilang;...
通讯作者:
Zhiyong Li
作者机构:
[Zhang, Xixin; Yang, Yuhang; Li, Zhiyong] Sichuan Agr Univ, Coll Informat Engn, Yaan 625000, Sichuan, Peoples R China.
[Li, Zhiyong] Sichuan Key Lab Agr Informat Engn, Yaan 625000, Sichuan, Peoples R China.
[Ning, Xin] Chinese Acad Sci, Inst Semicond, Beijing 100083, Peoples R China.
[Qin, Yilang] Henan Acad Agr Sci, Inst Agr Econ & Informat, Zhengzhou 450002, Henan, Peoples R China.
[Cai, Weiwei] Cent South Univ Forestry & Technol, Coll Logist & Transportat, Changsha 410004, Peoples R China.
通讯机构:
[Li, Z.] C
[Li, Z.] S
Sichuan Key Laboratory of Agricultural Information Engineering, Ya’an 625000, Sichuan, China<&wdkj&>College of Information Engineering, Sichuan Agricultural University, Ya’an 625000, Sichuan, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
semantic segmentation;farmland vacancy segmentation;strip pooling;crop growth assessment;encoder–decoder
期刊:
Entropy
ISSN:
1099-4300
年:
2021
卷:
23
期:
4
页码:
435-
基金类别:
Conceptualization: X.Z. and Y.Y.; methodology: X.N. and X.Z.; software: X.Z.; validation: X.Z., Y.Y. and Z.L.; formal analysis: Z.L.; investigation: Y.Y.; resources: X.N.; data curation: Y.Q.; writing—original draft preparation: X.Z.; writing—review and editing: X.N. and Z.L.; visualization: X.Z.; supervision: Y.Y.; project administration: Y.Q. and W.C.; funding acquisition: Z.L. and X.N. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Nature Science Foundation of China under Grant 61901436. General project of Education Department of Sichuan Province, Research on Intelligent Control System of New Agricultural Internet of Things Based on ZigBee Technology, Project No: 17ZB0336.
机构署名:
本校为其他机构
摘要:
In the research of green vegetation coverage in the field of remote sensing image segmentation, crop planting area is often obtained by semantic segmentation of images taken from high altitude. This method can be used to obtain the rate of cultivated land in a region (such as a country), but it does not reflect the real situation of a particular farmland. Therefore, this paper takes low-altitude images of farmland to build a dataset. After comparing several mainstream semantic segmentation algorithms, a new method that is more suitable for farmland vacancy segmentation is proposed. Additionall...

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