Cheng-wu CHEN, Tian-shu WANG, Kong-fa HU, Bei-hua BAO, Hui YAN, Xi-chen YANG. Identification Method of Pollen Typhae Processed Products Based on Convolutional Neural Network and Voting Mechanism[J]. Spectroscopy and Spectral Analysis, 2022, 42(11): 3361
- Spectroscopy and Spectral Analysis
- Vol. 42, Issue 11, 3361 (2022)
Fig. 1. Identification model of processed products of Pollen Typhae based on CNN and voting mechanism
Fig. 2. Raw spectral
Fig. 3. Partial convolution kernel of one-dimensional convolution pool
Fig. 4. Partial convolution kernel of two-dimensional convolution pool
Fig. 5. CNN eigenvectors of four pre-processing methods
(a): Unchanged preprocesses CNN eigenvectors; (b): SNV preprocesses CNN eigenvector;(c): First-order difference preprocesses CNN eigenvectors; (d): Min_max preprocesses CNN eigenvectors
(a): Unchanged preprocesses CNN eigenvectors; (b): SNV preprocesses CNN eigenvector;(c): First-order difference preprocesses CNN eigenvectors; (d): Min_max preprocesses CNN eigenvectors
Fig. 6. CNN test accuracy of four pre-processing methods
Fig. 7. Cross entropy loss of CNN based on four pre-processing methods
Fig. 8. Comparison of the proposed method with CNN, LDA and SNV-LDA in terms of test accuracy
Fig. 9. Test accuracy of different training set proportions
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Table 1. Weight distribution of different preprocessing methods
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