Fast Classification Method of Black Goji Berry (Lycium Ruthenicum Murr.) Based on Hyperspectral and Ensemble Learning

Wei LU; Miao-miao CAI; Qiang ZHANG; Shan LI

doi:10.3964/j.issn.1000-0593(2021)07-2196-09

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 7 >Page 2196 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 7, 2196 (2021)

Fast Classification Method of Black Goji Berry (Lycium Ruthenicum Murr.) Based on Hyperspectral and Ensemble Learning

Wei LU^1、1;, Miao-miao CAI^1、1;, Qiang ZHANG^2、2;, and Shan LI^3、3;

Author Affiliations

¹1. Jiangsu Provincial Laboratory of Modern Facility Agriculture Technology and Equipment Engineering, College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China

²2. School of Water Resources and Hydropower, Qinghai University, Xining 810016, China

³3. School of Life Science and Technology, Tongji University, Shanghai 200092, China

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DOI: 10.3964/j.issn.1000-0593(2021)07-2196-09 Cite this Article

Wei LU, Miao-miao CAI, Qiang ZHANG, Shan LI. Fast Classification Method of Black Goji Berry (Lycium Ruthenicum Murr.) Based on Hyperspectral and Ensemble Learning[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2196 Copy Citation Text

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References

[2] B Chu, J He, L Chen et al. Molecules, 23, 2395(2018).

[5] M Chao, S Zhu, J Zhang et al. Sensors, 19, 5225(2019).

[6] C Zhang, Y Xu, H Zhang et al. Infrared Physics & Technology, 102, 103034(2019).

[7] Y Huang, J Zhang, N Reddy K et al. Pest Management Science, 75, 3260(2019).

[8] H Ahn D, Y Choi J, C Kim H et al. Sensors, 19, 1560(2019).