Spectroscopy and Spectral Analysis, Volume. 41, Issue 8, 2598(2021)
Hyperspectral Image Features Combined With Spectral Features Used to Classify the Bruising Time of Peach
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Fig. 3. Spectra of samples without bruise and with different bruise time
Fig. 8. Score projection of the first three principal components (PCs) of all peaches
Table 1. Results of LS-SVM modeling based on the spectral features
View tableView in ArticleTable 1. Results of LS-SVM modeling based on the spectral features
输入
变量数碰伤时间
/hRBF_Kernel Lin_Kernel 误判数 正确率/% 误判数 正确率/% 176 12 6 80.00 9 76.67 176 24 1 96.67 1 96.67 176 36 0 100.00 1 96.67 176 48 0 100.00 0 100.00
Table 2. Results of LS-SVM modeling based on the image features
View tableView in ArticleTable 2. Results of LS-SVM modeling based on the image features
输入
变量数碰伤时间
/hRBF_Kernel Lin_Kernel 误判数 正确率/% 误判数 正确率/% 4 12 14 53.33 19 36.67 4 24 11 63.33 17 43.33 4 36 5 83.33 6 80.00 4 48 2 93.33 5 83.33
Table 3. Results of LS-SVM modeling based on the image features combined with spectral features
View tableView in ArticleTable 3. Results of LS-SVM modeling based on the image features combined with spectral features
输入
变量数碰伤时间
/hRBF_Kernel Lin_Kernel 误判数 正确率/% 误判数 正确率/% 180 12 5 83.33 10 66.67 180 24 1 96.67 2 93.33 180 36 0 100.00 6 80.00 180 48 0 100.00 5 83.33
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Ai-guo OUYANG, Hao-chen LIU, Long CHENG, Xiao-gang JIANG, Xiong LI, Xuan HU. Hyperspectral Image Features Combined With Spectral Features Used to Classify the Bruising Time of Peach[J]. Spectroscopy and Spectral Analysis, 2021, 41(8): 2598
Paper Information
Category: Research Articles
Received: Aug. 12, 2020
Accepted: --
Published Online: Sep. 8, 2021
The Author Email: OUYANG Ai-guo (ouyang1968711@163.com)
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