Table 5 Performance Analysis of SRB-VGG19.

From: Restricted Boltzmann machine with Sobel filter dense adversarial noise secured layer framework for flower species recognition

CNN models

Accuracy (%)

Mask-RCNN2

65.60

BPANN3

81.19

DeepLab5

79.70

DeepLab-ResNet9

80.90

FRCNN20

87.60

Deep CNN21

96.39

MobileNet37

83.30

ShuffleNetv2-Ghost32

88.40

AlexNet45

74.23

LeNet46,47

67.52

ResNet48,49,50

71.65

Inception51,52,53

66.23

Xception54

70.12

DenseNet55,56

83.17

VGG1957,58,59,60,61

81.36

Proposed SRB-VGG19 FCL

95.53

Proposed SRB-VGG19 Dense without ANL layer

98.65

SRB-VGG19 Dense ANL model with ANL layer

98.45

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