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. 2023 Sep 26;14:1256773. doi: 10.3389/fpls.2023.1256773

Table 3.

Comparison of the PMVT model with other backbone models on three datasets (the FPS indicator is calculated on the desktop computer, and bold text highlights the best-performing network).

Methods Top-1 Accuracy(%) Parameters (M) FLOPs (G) FPS (img/s)
Wheat Coffee Rice
SqueezeNet-1.0 70.0 79.7 86.2 0.74 0.73 293.0
SqueezeNet-1.1 86.1 83.1 85.1 0.73 0.26 311.5
ShuffleNetV2-1.0 89.6 68.5 82.7 1.27 0.15 151.9
MobileNetV3-Small 92.0 66.3 89.7 1.54 0.06 170.2
PMVT-XXS (ours) 93.6 85.4 93.1 0.98 0.31 88.5
ShuffleNetV2-1.5 92.5 73.0 86.2 2.50 0.31 148.4
MobileFormer-26M 91.4 77.5 90.8 2.22 0.03 53.1
MobileFormer-52M 92.8 79.2 83.9 2.46 0.05 60.7
MobileFormer-96M 92.8 84.2 87.3 3.33 0.09 58.8
MobileNetV3-Large 92.8 72.0 91.9 4.22 0.23 141.0
EfficientNet-B0 94.1 84.2 88.5 4.03 0.41 109.9
PMVT-XS (ours) 94.7 86.5 97.7 2.01 0.85 85.3
ShuffleNetV2-2.0 93.6 70.0 91.4 5.38 0.60 146.2
MobileFormer-151M 94.4 75.3 88.5 6.34 0.10 42.3
EfficientNet-B1 94.4 79.8 90.8 6.53 0.61 75.3
EfficientNet-B2 93.3 83.1 87.3 7.72 0.70 76.6
Deit-Tiny 91.4 78.7 84.0 5.49 1.08 161.7
PoolFormer-S12 91.4 85.4 85.1 11.39 1.81 178.3
CVT-Tiny 93.6 82.0 86.2 19.63 4.08 62.2
TNT-Small 92.8 80.9 88.5 23.40 4.85 67.3
ResNet50 93.9 70.8 90.8 23.53 4.13 125.1
ResNet101 94.1 63.0 88.5 42.50 7.86 66.3
PMVT-S (ours) 94.9 87.6 92.0 5.06 1.59 81.3