Classification of Near-infrared Spectroscopic Glucose Concentrations Using Convolutional Neural Network

被引:0
|
作者
Mekonnen, Bitewulign Kassa [1 ,2 ]
Yang, Webb [3 ,4 ]
Hsieh, Tung-Han [3 ]
Liaw, Shien-Kuei [1 ]
Yang, Fu-Liang [3 ]
机构
[1] Taiwan Tech, Grad Inst Electroopt Engn, Taipei, Taiwan
[2] Acad Sinica, Grad Inst Electroopt Engn, Taipei, Taiwan
[3] Acad Sinica, Res Ctr Appl Sci, Taipei, Taiwan
[4] NTU, Res Ctr Appl Sci, Taipei, Taiwan
关键词
convolutional neural network; near-infrared spectroscopy; classification;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
we explored the use of convolutional neural network for classification of near-infrared spectra measured from glucose aqueous with various concentrations. Our technique could be extended to other kinds of spectrums and benefit in different topics.
引用
收藏
页数:3
相关论文
共 50 条
  • [31] Analyzing Brain Functions by Subject Classification of Functional Near-Infrared Spectroscopy Data Using Convolutional Neural Networks Analysis
    Hiwa, Satoru
    Hanawa, Kenya
    Tamura, Ryota
    Hachisuka, Keisuke
    Hiroyasu, Tomoyuki
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2016, 2016
  • [32] Backpropagation Artificial Neural Network for Determination of Glucose Concentration from Near-infrared Spectra
    Malik, Bilal Ahmad
    Naqash, Asma
    Bhat, G. M.
    2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 2688 - 2691
  • [33] Detection of Adulteration in Infant Formula Based on Ensemble Convolutional Neural Network and Near-Infrared Spectroscopy
    Liu, Yisen
    Zhou, Songbin
    Han, Wei
    Li, Chang
    Liu, Weixin
    Qiu, Zefan
    Chen, Hong
    FOODS, 2021, 10 (04)
  • [34] Wood quality of Chinese zither panel based on convolutional neural network and near-infrared spectroscopy
    Huang, Yinglai
    Meng, Shiyu
    Zhao, Peng
    Li, Chao
    APPLIED OPTICS, 2019, 58 (18) : 5122 - 5127
  • [35] Wood Quality of Chinese Zither Panels Based on Convolutional Neural Network and Near-Infrared Spectroscopy
    Meng Shi-yu
    Huang Ying-lai
    Zhao Peng
    Li Chao
    Liu Zhen-bo
    Liu Yi-xing
    Xu Yan
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40 (01) : 284 - 289
  • [36] Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra
    Ng, Wartini
    Minasny, Budiman
    Montazerolghaem, Maryam
    Padarian, Jose
    Ferguson, Richard
    Bailey, Scarlett
    McBratney, Alex B.
    GEODERMA, 2019, 352 : 251 - 267
  • [37] Development of a calibration model for near infrared spectroscopy using a convolutional neural network
    Li, Menghu
    Pan, Tianhong
    Bai, Yang
    Chen, Qi
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2022, 30 (02) : 89 - 96
  • [38] Neural Network for Classification of Chinese Zither Panel Wood via Near-infrared Spectroscopy
    Huang, Yinglai
    Meng, Shiyu
    Hwang, Sung-Wook
    Kobayashi, Kayoko
    Sugiyama, Junji
    BIORESOURCES, 2020, 15 (01) : 130 - 141
  • [39] Identification of softwood species using convolutional neural networks and raw near-infrared spectroscopy
    Pan, Xi
    Qiu, Jian
    Yang, Zhong
    WOOD MATERIAL SCIENCE & ENGINEERING, 2023, 18 (04) : 1338 - 1348
  • [40] Using near-infrared spectroscopy in the classification of white and iberian pork with neural networks
    Guillen, Alberto
    del Moral, F. G.
    Herrera, L. J.
    Rubio, G.
    Rojas, I.
    Valenzuela, O.
    Pomares, H.
    NEURAL COMPUTING & APPLICATIONS, 2010, 19 (03): : 465 - 470