基于荧光光谱法与深度信念网络的稻种发芽率检测方法研究
卢伟, 郭阳鸣, 代德建, 张澄宇, 王新宇. 基于荧光光谱法与深度信念网络的稻种发芽率检测方法研究[J]. 光谱学与光谱分析, 2018, 38(4): 1303.
LU Wei, GUO Yang-ming, DAI De-jian, ZHANG Cheng-yu, WANG Xin-yu. Rice Germination Rate Detection Based on Fluorescent Spectrometry and Deep Belief Network[J]. Spectroscopy and Spectral Analysis, 2018, 38(4): 1303.
[1] Sharif M K, Butt M S, Anjum F M, et al. Critical Reviews in Food Science and Nutrition, 2014, 54(6): 807.
[2] Paiva E P, Torres S B, Almeida J P N D, et al. Revista Ciência Agronmica, 2017, 48(1): 118.
[3] Na Y W, Shim S I, Chung J S, et al. Korean Journal of Crop Science, 2014, 59(2): 188.
[4] Lohumi S, Mo C, Cho B K, et al. Journal of Biosystems Engineering, 2013, 38(4): 312.
[5] Song L, Wang Q, Wang C, et al. Journal of Stored Products Research, 2015, 62: 46.
[6] Yu S M, Lu W, Ding D, et al. Laser & Optoelectronics Progress, 2016, 53(1): 113.
[7] Fang W H, Lu W, Xu H L, et al. Spectroscopy and Spectral Analysis, 2016, 36(8): 2692.
[8] Li H, Lu W, Du C, et al. Chinese Journal of Lasers, 2015, 42(11): 1115003.
[9] Fang W, Lu W, Hong D, et al. Optics Journal, 2015, 35(10): 111.
[10] Lu L, Tian S, Zhang J, et al. PLoS One, 2013, 8(2): e57360.
[11] Ambrose A, Lohumi S, Lee W H, et al. Sensors & Actuators B Chemical, 2016, 224: 500.
[12] Yang J, Gong W, Shi S, et al. Scientific Reports, 2016, 6: 28787.
[13] Chen Q, Qi S, Li H, et al. Spectrochimica Acta Part A Molecular & Biomolecular Spectroscopy, 2014, 131(19): 177.
[14] Agati G, Foschi L, Grossi N, et al. European Journal of Agronomy, 2013, 45: 39.
[15] Sergiel I, Pohi P, Biesaga M, et al. Food Chemistry, 2014, 145: 319.
[16] Ko K Y, Lee C A, Choi J C, et al. Food Additives & Contaminants Part A Chemistry Analysis Control Exposure & Risk Assessment, 2014, 31(9): 1451.
[17] Singhal V, Gogna A, Majumdar A. Deep Dictionary Learning vs Deep Belief Network vs Stacked Autoencoder: An Empirical Analysis. International Conference on Neural Information Processing. Springer International Publishing, 2016. 337.
[18] Shaban M. International Journal of Agriculture and Crop Sciences, 2013, 6(11): 627.
[19] Kaewkham T, Russell K H, Boonmee S. Biocontrol Science and Technology, 2016, 26(8): 1048.
[20] Yang H, Fu Y B. Frontiers in Plant Science, 2016, 7: 1474.
[21] Mala D M, Yoshimura M, Kawasaki S, et al. LWT-Food Science and Technology, 2016, 68: 14.
[22] Zhang Y, Liu B, Ji X, et al. Neural Processing Letters, 2017, 45(2): 365.
[23] vokelj M, Samo Z, Ivan P. Journal of Sound and Vibration, 2016, 370: 394.
[24] Jolliffe I T, Jorge C. Phil. Trans. R. Soc. A, 2016, 374: 20150202.
[25] Bro R, Age K S. Analytical Methods, 2014, 6(9): 2812.
[26] Wang L, Zeng Y, Chen T. Expert Systems with Applications, 2015, 42(2): 855.
[27] Lian R J. IEEE Transactions on Industrial Electronics, 2014, 61(3): 1493.
[28] O’Connor P, Neil D, Liu S C, et al. Frontiers in Neuroscience, 2013, 7(178): 1.
[29] Kuremoto Takashi, Shinsuke K, Kunikazu K, et al. Neurocomputing, 2014, 137: 47.
[30] Elena A G, Alexander N T, Folkert A H. Plant Physiology, 1997, 114: 383.
[31] Olivier L, Frans J M H, Julia B, et al. Plant Physiology, 2000, 122(2): 597.
[32] Brits G J, Brown N A C, Calitz F J, et al. South African Journal of Botany, 2015, 97: 1.
[33] Zhao Q, Lv Q, Wang H. Biosensors and Bioelectronics, 2015, 70: 188.
卢伟, 郭阳鸣, 代德建, 张澄宇, 王新宇. 基于荧光光谱法与深度信念网络的稻种发芽率检测方法研究[J]. 光谱学与光谱分析, 2018, 38(4): 1303. LU Wei, GUO Yang-ming, DAI De-jian, ZHANG Cheng-yu, WANG Xin-yu. Rice Germination Rate Detection Based on Fluorescent Spectrometry and Deep Belief Network[J]. Spectroscopy and Spectral Analysis, 2018, 38(4): 1303.
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