Spectroscopy and Spectral Analysis, Volume. 42, Issue 5, 1620(2022)
Comparison of Machine Learning Algorithms for Remote Sensing Monitoring of Rice Yields
[3] Liu X D, Sun Q H[D]. International Journal of Pest Management, 62, 205(2016).
[6] Ikeura H, Kawamura K, Phongchanmaixay S et al[D]. Remote Sensing, 10, 1249(2018).
[8] Bennett K P, Parrado-Hernández E[D]. Journal of Machine Learning Research, 7, 1265(2006).
[9] Busato P, Liakos K G, Moshou D[D]. Sensors, 18, 2674(2018).
[10] Bao Y, Mi C, Wu N et al[D]. Applied Sciences, 9, 4119(2019).
[12] Curran P J, Dungan J L, Macler B A et al[D]. Remote Sensing of Environment, 39, 153(1992).
[14] Bahrami H A, Davari M, Karimi S A et al[D]. CATENA, 197, 104987(2021).
[15] Bona E, de Oliveira J F, dos Santos F R et al[D]. Spectrochimica Acta Part B: Atomic Spectroscopy, 175, 106016(2021).
[16] Assaf A G, Tasiopoulos A, Tsionas M[D]. Tourism Management, 71, 1(2019).
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Xia JING, Jie ZHANG, Jiao-jiao WANG, Shi-kang MING, You-qiang FU, Hai-kuan FENG, Xiao-yu SONG. Comparison of Machine Learning Algorithms for Remote Sensing Monitoring of Rice Yields[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1620
Category: Research Articles
Received: Sep. 30, 2021
Accepted: --
Published Online: Nov. 10, 2022
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