Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image

Rong-hua GAO; Lu FENG; Yue ZHANG; Ji-dong YUAN; Hua-rui WU; Jing-qiu GU

doi:10.3964/j.issn.1000-0593(2022)10-3226-09

Spectroscopy and Spectral Analysis, Volume. 42, Issue 10, 3226(2022)

Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image

Rong-hua GAO^1、*, Lu FENG^{1、1; 2; *;}, Yue ZHANG^3、3;, Ji-dong YUAN^3、3;, Hua-rui WU^{1、1; 2;}, and Jing-qiu GU^{1、1; 2;}

Author Affiliations

¹1. Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China

³3. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China

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References(4)

[7] Sun Jun, Wu Xiaohong, Zhou Xin et al[D]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 212, 215(2019).

[9] Pan Y C, Yang Guijun, Zhang Ning et al[D]. Remote Sensing, 12, 3188(2020).

[10] He Y, Xie C, Yang C[D]. Computers and Electronics in Agriculture, 135, 154(2017).

[11] Lucas B, Pelletier C, Shifaz A et al[D]. Data Mining and Knowledge Discovery, 33, 607(2019).

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Rong-hua GAO, Lu FENG, Yue ZHANG, Ji-dong YUAN, Hua-rui WU, Jing-qiu GU. Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image[J]. Spectroscopy and Spectral Analysis, 2022, 42(10): 3226

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Paper Information

Category: Research Articles

Received: Aug. 11, 2021

Accepted: Mar. 28, 2022

Published Online: Nov. 23, 2022

The Author Email: Rong-hua GAO (gaorh@nercita.org.cn)

DOI:10.3964/j.issn.1000-0593(2022)10-3226-09

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