基于全卷积神经网络的黄花梨采收期可见-近红外光谱检测方法
[1] Sharpe P, Barber H. Applied Optics, 1972, 11(12): 2902.
[2] Peirs A, Lammertyn J, Ooms K, et al. Postharvest Biology and Technology, 2001, 21(2): 189.
[3] Peirs A, Schenk A, Nicola B M. Postharvest Biology and Technology, 2005, 35(1): 1.
[4] Zude M, Herold B, Roger J M, et al. Journal of Food Engineering, 2006, 77(2): 254.
[5] Liew C Y, Lau C Y. Int. Food Res. J, 2012, 19(2): 751.
[6] ZHAO Juan, QUAN Peng-kun, MA Min-juan, et al(赵 娟, 全朋坤, 马敏娟, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2018, 49(12): 354.
[7] McCormick R, Biegert K. NIR News, 2019, 30(1): 12.
[8] Malek S, Melgani F, Bazi Y. Journal of Chemometrics, 2018, 32(5): e2977.
[9] Bjerrum E, Glahder M, Skov T. arXiv preprint arXiv: 1710.01927, 2017.
[11] Acquarelli J, Van Laarhoven T, Gerretzen J, et al. Analytica Chimica Acta, 2017, 954: 22.
[12] Cui C, Fearn T. Chemometrics and Intelligent Laboratory Systems, 2018, 182: 9.
刘辉军, 魏超宇, 韩文, 姚燕. 基于全卷积神经网络的黄花梨采收期可见-近红外光谱检测方法[J]. 光谱学与光谱分析, 2020, 40(9): 2932. LIU Hui-jun, WEI Chao-yu, HAN Wen, YAO Yan. Determination of Huanghua Pear’s Harvest Time Based on Convolutional Neural Networks by Visible-Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2020, 40(9): 2932.