深度卷积网络的多品种多厂商药品近红外光谱分类
[1] Ma H L, Wang J W, Chen Y J, et al. Food Chemistry, 2017, 215: 108.
[2] Lê L M M, Eveleigh L, Hasnaoui I, et al. Journal of Pharmaceutical and Biomedical Analysis, 2017, 138: 249.
[3] Xue J T, Ye L M, Li C Y, et al. Optik, 2018, 170: 30.
[4] Risoluti R, Materazzi S, Gregori A, et al. Talanta, 2016, 153: 407.
[5] Deconinck E, Sacré P Y, Coomans D, et al. Journal of Pharmaceutical and Biomedical Analysis, 2012, 57: 68.
[6] ZHANG Wei-dong, LI Ling-qiao, HU Jin-quan, et al(张卫东, 李灵巧, 胡锦泉, 等). Chinese Journal of Analytical Chemistry(分析化学), 2018, 46(9): 1446.
[7] Yang H H, Hu B C, Pan X P, et al. Journal of Innovative Optical Health Sciences, 2016, 10(2): 1630011.
[8] Lecun Y, Bengio Y, Hinton G. Nature, 2015, 521(7553): 436.
[9] Nassif A B, Shahin I, Attili I, et al. IEEE Access, 2019, 7: 19143.
[10] Lai D, Tian W, Chen L. Pattern Recognition, 2019, 88: 547.
[12] Acquarelli J, Laarhoven T V, Gerretzen J, et al. Analytica Chimica Acta, 2017, 954: 22.
[13] Srivastava N, Hinton G, Krizhevsky A, et al. Journal of Machine Learning Research, 2014, 15(1): 1929.
李灵巧, 潘细朋, 冯艳春, 尹利辉, 胡昌勤, 杨辉华. 深度卷积网络的多品种多厂商药品近红外光谱分类[J]. 光谱学与光谱分析, 2019, 39(11): 3606. LI Ling-qiao, PAN Xi-peng, FENG Yan-chun, YIN Li-hui, HU Chang-qin, YANG Hui-hua. Deep Convolution Network Application in Identification of Multi-Variety and Multi-Manufacturer Pharmaceutical[J]. Spectroscopy and Spectral Analysis, 2019, 39(11): 3606.