Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.

Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.

<p>Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.</p>

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Bibliographic Details
Main Author:	Syeda Nazia Ashraf (17541222) (author)
Other Authors:	Raheel Siddiqi (19923944) (author), Humera Farooq (19923947) (author)
Published:	2024
Subjects:	Biotechnology Immunology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified reducing overall accuracy projected gradient descent carefully crafted perturbations automating routine tasks also save time called stack model reliable defense framework multiple attack types based model receives autoencoder improves accuracy single defense mechanism reliable defense mechanism based models may based defense mechanism various adversarial attacks popular adversarial attacks detect adversarial attacks art attacks carried original medical images based pneumonia detection pgd attack using perturbed medical image pneumonia detection models vgg16 model shows defense mechanism based models adversarial attack adversarial attacks medical images hybrid model adversarial images robust detection defense strategies trained models convolutional autoencoder art studies pgd attacks ray images two state two pre treatment planning study shows significant hurdle one type often imperceptible launch cyber human eye five magnitudes facilitating radiologists even though earlier studies deep learning chest x auto encoder added perturbation 67 %.
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