• Laser & Optoelectronics Progress
  • Vol. 57, Issue 15, 153005 (2020)
Xiaobin Wang1, Xiao Ma1, and Xincheng Wang2、*
Author Affiliations
  • 1School of Forensic Science, People's Public Security University of China, Beijing 100038, China
  • 2School of Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
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    DOI: 10.3788/LOP57.153005 Cite this Article Set citation alerts
    Xiaobin Wang, Xiao Ma, Xincheng Wang. Infrared Spectral Pattern Recognition of Watercolor Pen Ink Based on Artificial Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(15): 153005 Copy Citation Text show less
    Compression results of infrared spectrum
    Fig. 1. Compression results of infrared spectrum
    Structure of ANN
    Fig. 2. Structure of ANN
    Classification results and accuracy
    Fig. 3. Classification results and accuracy
    ROC curves. (a) Training set; (b) validation set; (c) test set; (d) total ROC curve of overall
    Fig. 4. ROC curves. (a) Training set; (b) validation set; (c) test set; (d) total ROC curve of overall
    Compression timeXRMSE
    12.0×10-3
    22.4×10-3
    31.9×10-1
    42.1×10-1
    54.0×10-1
    Table 1. XRMSE at different compression times
    Sample categoryCharacteristic wave numbers
    12345678910
    1334030101620396035509912790126020401140
    234303140108011702260903251035702820976
    33360230030301330972355099591831701430
    Table 2. Characteristic wave numbers of different kinds of samplesunit: cm-1
    Xiaobin Wang, Xiao Ma, Xincheng Wang. Infrared Spectral Pattern Recognition of Watercolor Pen Ink Based on Artificial Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(15): 153005
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