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Table 4 Comparative analysis of precision, recall and F-measure for existing DSCOP and proposed NSVM-CNN

From: An effective image retrieval based on optimized genetic algorithm utilized a novel SVM-based convolutional neural network classifier

No of image retrieved

Corel 1K dataset

Precision

Recall

F-measure

DSCOP

NSVM-CNN

DSCOP

NSVM-CNN

DSCOP

NSVM-CNN

10

80

99.52

9

93.45

16.17978

96.38953

20

75

99.46

15

93.97

25

96.63709

30

72

99.32

21

94.49

32.51613

96.84482

40

69

99.23

28

95.01

39.83505

97.07416

50

65

99.13

32

95.53

42.8866

97.29671

60

63

99.03

38

96.05

47.40594

97.51724

70

60

98.93

42

96.57

49.41176

97.73576

80

59

98.83

47

97.09

52.32075

97.95227

90

57

98.73

50

97.61

53.27103

98.16681

100

55

98

55

98

55

98