Visualization of adversarial samples.
<p>(a) represents the original image and (b)-(f) represent the adversarial examples generated by five methods.</p>
Պահպանված է:
| Հիմնական հեղինակ: | |
|---|---|
| Այլ հեղինակներ: | |
| Հրապարակվել է: |
2025
|
| Խորագրեր: | |
| Ցուցիչներ: |
Ավելացրեք ցուցիչ
Չկան պիտակներ, Եղեք առաջինը, ով նշում է այս գրառումը!
|
| _version_ | 1849927625931227136 |
|---|---|
| author | Chen Lin (95910) |
| author2 | Sheng Long (14795824) |
| author2_role | author |
| author_facet | Chen Lin (95910) Sheng Long (14795824) |
| author_role | author |
| dc.creator.none.fl_str_mv | Chen Lin (95910) Sheng Long (14795824) |
| dc.date.none.fl_str_mv | 2025-11-25T18:43:47Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0337463.g004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Visualization_of_adversarial_samples_/30715103 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Neuroscience Biological Sciences not elsewhere classified Information Systems not elsewhere classified two crucial metrics nesterov &# 8217 natural data distribution introduces nesterov ’ goals often conflict generation process toward extensive experiments demonstrate deep neural networks achieving stealthy attacks imperceptible perturbations tend evaluating adversarial attacks div >< p diffusion mechanism guides imperceptible adversarial examples imperceptible perturbations adversarial attacks box attacks strong acceleration size strategy perform poorly novel framework mislead models highly vulnerable generalization capabilities art methods adding subtle adaptive step accelerated gradient |
| dc.title.none.fl_str_mv | Visualization of adversarial samples. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>(a) represents the original image and (b)-(f) represent the adversarial examples generated by five methods.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_83960aae82abbbe35d97304eb97eb4bc |
| identifier_str_mv | 10.1371/journal.pone.0337463.g004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30715103 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Visualization of adversarial samples.Chen Lin (95910)Sheng Long (14795824)NeuroscienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedtwo crucial metricsnesterov &# 8217natural data distributionintroduces nesterov ’goals often conflictgeneration process towardextensive experiments demonstratedeep neural networksachieving stealthy attacksimperceptible perturbations tendevaluating adversarial attacksdiv >< pdiffusion mechanism guidesimperceptible adversarial examplesimperceptible perturbationsadversarial attacksbox attacksstrong accelerationsize strategyperform poorlynovel frameworkmislead modelshighly vulnerablegeneralization capabilitiesart methodsadding subtleadaptive stepaccelerated gradient<p>(a) represents the original image and (b)-(f) represent the adversarial examples generated by five methods.</p>2025-11-25T18:43:47ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0337463.g004https://figshare.com/articles/figure/Visualization_of_adversarial_samples_/30715103CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307151032025-11-25T18:43:47Z |
| spellingShingle | Visualization of adversarial samples. Chen Lin (95910) Neuroscience Biological Sciences not elsewhere classified Information Systems not elsewhere classified two crucial metrics nesterov &# 8217 natural data distribution introduces nesterov ’ goals often conflict generation process toward extensive experiments demonstrate deep neural networks achieving stealthy attacks imperceptible perturbations tend evaluating adversarial attacks div >< p diffusion mechanism guides imperceptible adversarial examples imperceptible perturbations adversarial attacks box attacks strong acceleration size strategy perform poorly novel framework mislead models highly vulnerable generalization capabilities art methods adding subtle adaptive step accelerated gradient |
| status_str | publishedVersion |
| title | Visualization of adversarial samples. |
| title_full | Visualization of adversarial samples. |
| title_fullStr | Visualization of adversarial samples. |
| title_full_unstemmed | Visualization of adversarial samples. |
| title_short | Visualization of adversarial samples. |
| title_sort | Visualization of adversarial samples. |
| topic | Neuroscience Biological Sciences not elsewhere classified Information Systems not elsewhere classified two crucial metrics nesterov &# 8217 natural data distribution introduces nesterov ’ goals often conflict generation process toward extensive experiments demonstrate deep neural networks achieving stealthy attacks imperceptible perturbations tend evaluating adversarial attacks div >< p diffusion mechanism guides imperceptible adversarial examples imperceptible perturbations adversarial attacks box attacks strong acceleration size strategy perform poorly novel framework mislead models highly vulnerable generalization capabilities art methods adding subtle adaptive step accelerated gradient |