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. 2022 Apr 16;11(8):1156. doi: 10.3390/foods11081156

Table 4.

Results of MobileViT-xs training using G1 and G2 data.

Sample Size DA Method BLACK (%) DBS (%) QC (%) SLH (%) XBS (%) AIA (%)
N None 86.2 ± 2.67 86.23 ± 1.41 90.78 ± 2.76 91.94 ± 1.77 87.48 ± 1.63 /
2N Erasing × 1 92.33 ± 0.85 89.15 ± 0.74 96.36 ± 0.68 94.98 ± 0.32 92.18 ± 1.46 4.47
Noise × 1 91.32 ± 0.9 87.68 ± 1.36 95.36 ± 1.99 94.06 ± 1.04 91.23 ± 1.76 3.4
Rotation × 1 93.21 ± 0.6 89.72 ± 1.35 97.59 ± 0.29 95.65 ± 0.64 94.17 ± 0.96 5.54
DSM × 1 92.81 ± 0.89 90.38 ± 1.61 97.87 ± 0.58 96.0 ± 0.4 95.08 ± 1.58 5.9

N, the data amount of the original training sample; 2N, the sample size after once augmentation; DA, data augmentation; None, original data; Erasing, random erasing; Noise, random noise; Rotation, rotation; DSM, difference of spectral mean; BLACK, Black peanut; DBS, Dabaisha; QC, Qicai; SLH, Silihong; XBS, Xiaobaisha; AIA, the average improved accuracy.