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>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Syeda Nazia Ashraf (17541222) (author)
مؤلفون آخرون:	Raheel Siddiqi (19923944) (author), Humera Farooq (19923947) (author)
منشور في:	2024
الموضوعات:	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 %.
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

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author	Syeda Nazia Ashraf (17541222)
author2	Raheel Siddiqi (19923944) Humera Farooq (19923947)
author2_role	author author
author_facet	Syeda Nazia Ashraf (17541222) Raheel Siddiqi (19923944) Humera Farooq (19923947)
author_role	author
dc.creator.none.fl_str_mv	Syeda Nazia Ashraf (17541222) Raheel Siddiqi (19923944) Humera Farooq (19923947)
dc.date.none.fl_str_mv	2024-10-21T17:34:51Z
dc.identifier.none.fl_str_mv	10.1371/journal.pone.0307363.t013
dc.relation.none.fl_str_mv	https://figshare.com/articles/dataset/Precision_recall_sensitivity_and_F1_score_before_and_after_FGSM_and_PGD_attacks_/27271886
dc.rights.none.fl_str_mv	CC BY 4.0 info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv	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 %.
dc.title.none.fl_str_mv	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
dc.type.none.fl_str_mv	Dataset info:eu-repo/semantics/publishedVersion dataset
description	<p>Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.</p>
eu_rights_str_mv	openAccess
id	Manara_2dce5e360287d57476ab3b2ffd09e6e2
identifier_str_mv	10.1371/journal.pone.0307363.t013
network_acronym_str	Manara
network_name_str	ManaraRepo
oai_identifier_str	oai:figshare.com:article/27271886
publishDate	2024
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv	CC BY 4.0
spelling	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.Syeda Nazia Ashraf (17541222)Raheel Siddiqi (19923944)Humera Farooq (19923947)BiotechnologyImmunologyScience PolicySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedreducing overall accuracyprojected gradient descentcarefully crafted perturbationsautomating routine tasksalso save timecalled stack modelreliable defense frameworkmultiple attack typesbased model receivesautoencoder improves accuracysingle defense mechanismreliable defense mechanismbased models maybased defense mechanismvarious adversarial attackspopular adversarial attacksdetect adversarial attacksart attacks carriedoriginal medical imagesbased pneumonia detectionpgd attack usingperturbed medical imagepneumonia detection modelsvgg16 model showsdefense mechanismbased modelsadversarial attackadversarial attacksmedical imageshybrid modeladversarial imagesrobust detectiondefense strategiestrained modelsconvolutional autoencoderart studiespgd attacksray imagestwo statetwo pretreatment planningstudy showssignificant hurdleone typeoften imperceptiblelaunch cyberhuman eyefive magnitudesfacilitating radiologistseven thoughearlier studiesdeep learningchest xauto encoderadded perturbation67 %.<p>Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.</p>2024-10-21T17:34:51ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0307363.t013https://figshare.com/articles/dataset/Precision_recall_sensitivity_and_F1_score_before_and_after_FGSM_and_PGD_attacks_/27271886CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/272718862024-10-21T17:34:51Z
spellingShingle	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks. Syeda Nazia Ashraf (17541222) 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 %.
status_str	publishedVersion
title	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
title_full	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
title_fullStr	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
title_full_unstemmed	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
title_short	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
title_sort	Precision, recall (sensitivity) and F1 score before and after FGSM and PGD attacks.
topic	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 %.

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

مواد مشابهة