Table 7 The assessment of the image detection run by the 5 transfer learning algorithms.

Notebook Computer

91.27

90.85

91.79

92.60

93.22

94.21

Bicycle

94.86

93.57

91.33

92.80

93.03

96.05

Zebra

93.57

91.37

92.57

91.78

92.76

93.72

Flower

92.49

91.05

92.42

91.61

93.18

95.48

Experimental Methods

Precision(%)

Experimental Images

MTSL-DRDR

TATD

SRW

DTR

HDARMST

IFDAFHTL

Notebook computer

90.85

91.54

91.61

91.74

92.08

92.54

Bicycle

91.15

92.06

90.21

92.07

91.76

93.07

Zebra

90.37

91.31

91.64

90.46

92.39

91.23

Flower

91.60

90.90

90.32

91.26

91.69

92.19

Experimental Methods

Recall(%)

Experimental Images

MTSL-DRDR

TATD

SRW

DTR

HDARMST

IFDAFHTL

Notebook Computer

81.57

84.38

86.49

87.22

86.72

89.12

Bicycle

80.44

85.56

83.55

86.44

86.01

87.39

Zebra

83.29

83.04

84.21

83.25

85.47

86.80

Flower

82.07

85.73

86.36

84.93

86.03

88.47

Experimental methods

SSIM [0,1]

Experimental Images

MTSL-DRDR

TATD

SRW

DTR

HDARMST

IFDAFHTL

Notebook Computer

0.82

0.83

0.83

0.86

0.87

0.89

Bicycle

0.80

0.85

0.86

0.85

0.90

0.92

Zebra

0.84

0.88

0.81

0.87

0.84

0.90

Flower

0.85

0.84

0.82

0.81

0.82

0.87

Experimental Methods

PSNR(Effective Value ≥ 40)

Experimental Images

MTSL-DRDR

TATD

SRW

DTR

HDARMST

IFDAFHTL

Notebook Computer

40.11

40.39

41.68

41.35

41.62

42.33

Bicycle

39.84

41.51

41.39

40.72

40.91

41.97

Zebra

38.97

41.34

40.26

41.69

41.55

43.06

Flower

39.26

40.87

42.08

40.31

41.35

42.79