Table 2 Vehicle detection results of the VDTC-CEOADL algorithm in VEDAI dataset.

From: Optimal deep learning based vehicle detection and classification using chaotic equilibrium optimization algorithm in remote sensing imagery

Class

Accuy

Sensy

Specy

Fscore

AUCscore

Training phase (80%)

 Car

97.73

98.25

97.42

96.96

97.84

 Truck

98.64

90.83

99.34

91.60

95.08

 Van

98.78

71.25

99.55

76.00

85.40

 Pickup car

98.81

98.93

98.77

97.70

98.85

 Boat

99.39

92.70

99.72

93.38

96.21

 Camping car

98.37

93.49

98.94

92.28

96.21

 Other

99.12

88.05

99.75

91.50

93.90

 Plane

99.12

41.46

99.93

56.67

70.70

 Tractor

99.12

89.04

99.64

90.91

94.34

 Average

98.79

84.89

99.23

87.44

92.06

Testing phase (20%)

 Car

98.10

98.02

98.15

97.24

98.08

 Truck

98.64

93.33

99.12

91.80

96.22

 Van

99.19

70.00

100.00

82.35

85.00

 Pickup car

98.78

99.50

98.52

97.78

99.01

 Boat

99.05

87.88

99.57

89.23

93.73

 Camping car

98.64

96.39

98.93

94.12

97.66

 Other

99.46

92.68

99.86

95.00

96.27

 Plane

99.46

33.33

100.00

50.00

66.67

 Tractor

99.46

90.91

100.00

95.24

95.45

 Average

98.98

84.67

99.35

88.08

92.01