• Infrared and Laser Engineering
  • Vol. 50, Issue 3, 20200399 (2021)
Guojun Shi
Author Affiliations
  • College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China
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    DOI: 10.3788/IRLA20200399 Cite this Article
    Guojun Shi. Target recognition method of infrared imagery via joint representation of deep features[J]. Infrared and Laser Engineering, 2021, 50(3): 20200399 Copy Citation Text show less
    CNN architecture for infrared imagery target recognition
    Fig. 1. CNN architecture for infrared imagery target recognition
    Illustration of infrared imagery target recognition via joint representation of deep features
    Fig. 2. Illustration of infrared imagery target recognition via joint representation of deep features
    Labels and illustrations of the 10 targets in MWIR dataset
    Fig. 3. Labels and illustrations of the 10 targets in MWIR dataset
    Confusion matrix of the proposed method for original test samples
    Fig. 4. Confusion matrix of the proposed method for original test samples
    Comparison of recognition results on the noisy test samples with different methods
    Fig. 5. Comparison of recognition results on the noisy test samples with different methods
    Comparison of recognition results under reduced training sets with different methods
    Fig. 6. Comparison of recognition results under reduced training sets with different methods
    MethodAverage recognition rate
    Proposed97.7%
    SVM94.5%
    SRC95.1%
    JSR96.6%
    CNN97.2%
    Table 1. [in Chinese]
    Guojun Shi. Target recognition method of infrared imagery via joint representation of deep features[J]. Infrared and Laser Engineering, 2021, 50(3): 20200399
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