Table 3 Comparison of the performance of different models.

From: Recognition model for counterfeit protection system in colour-laser-printed documents based on improved ShuffleNet V2

Model

Accuracy/%

Precision/

%

Recall/

%

F1-score/

%

FLOPs

Parameters

Inference

time/ms

EfficientNet_b0

87.33 ± 0.68

87.61 ± 0.75

86.94 ± 0.76

87.11 ± 0.78

4.11 × 108

4.01 × 106

54.85

Inception_v3

88.00 ± 0.95

88.18 ± 1.05

87.76 ± 1.12

87.80 ± 0.97

2.86 × 109

2.38 × 107

108.64

MobileNet_v2

84.50 ± 0.87

85.53 ± 0.82

84.12 ± 0.78

84.33 ± 0.79

3.27 × 108

3.50 × 106

40.62

MobileNetV3_small_100

72.40 ± 1.25

74.34 ± 1.22

72.16 ± 1.17

72.42 ± 1.28

6.12 × 107

1.52 × 106

35.18

ShuffleNet V2 1 × 

83.82 ± 0.42

84.49 ± 0.58

82.30 ± 0.54

83.45 ± 0.58

1.52 × 108

2.28 × 106

38.83

ResNext50_32 × 4d

84.95 ± 0.62

85.13 ± 0.71

84.84 ± 0.68

84.75 ± 0.57

4.29 × 109

2.50 × 107

107.45

ResNet50

70.81 ± 0.54

72.70 ± 0.62

71.05 ± 0.45

71.06 ± 0.57

4.13 × 109

2.55 × 107

83.12

Xception

91.18 ± 1.05

91.32 ± 0.92

90.90 ± 1.11

90.98 ± 0.94

4.60 × 109

2.08 × 107

101.25

DensNet121

82.69 ± 0.87

83.76 ± 0.78

82.50 ± 0.92

82.80 ± 0.86

2.90 × 109

7.98 × 106

116.86

ShuffleNet_OD_CA

91.18 ± 0.45

91.49 ± 0.56

91.04 ± 0.58

91.14 ± 0.53

8.03 × 107

1.82 × 106

36.96