Table 8 Effect of adversarial training on retrieval performance for normal and adversarial queries across different backbone networks and Hashcode lengths on the A-MRI dataset.

From: Secure and fault tolerant cloud based framework for medical image storage and retrieval in a distributed environment

Backbone Network

Query Type

Adversarial Training

Hashcode Length

8 bits

16 bits

32 bits

64 bits

AlexNet

Normal

No

0.79

0.89

0.87

0.75

Adversary

No

0.03

0.08

0.02

0.07

Normal

Yes

0.69

0.80

0.78

0.62

Adversary

Yes

0.65

0.76

0.67

0.54

VGG 16

Normal

No

0.77

0.86

0.86

0.74

Adversary

No

0.01

0.06

0.08

0.05

Normal

Yes

0.73

0.81

0.84

0.74

Adversary

Yes

0.70

0.80

0.73

0.57

DenseNet 121

Normal

No

0.78

0.84

0.81

0.68

Adversary

No

0.12

0.11

0.11

0.02

Normal

Yes

0.75

0.83

0.79

0.65

Adversary

Yes

0.70

0.80

0.75

0.59

DeneNet 201

Normal

No

0.79

0.88

0.82

0.71

Adversary

No

0.01

0.05

0.16

0.08

Normal

Yes

0.77

0.86

0.80

0.69

Adversary

Yes

0.76

0.84

0.77

0.60

ConvNeXt (Ours)

Normal

No

0.81

0.89

0.84

0.73

Adversary

No

0.01

0.05

0.03

0.01

Normal

Yes

0.80

0.88

0.84

0.73

Adversary

Yes

0.73

0.83

0.75

0.61