Matches in SemOpenAlex for { <https://semopenalex.org/work/W3087932236> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3087932236 endingPage "102834" @default.
- W3087932236 startingPage "102834" @default.
- W3087932236 abstract "Machine learning is becoming increasingly popular in modern technology and has been adopted in various application areas. However, researchers have demonstrated that machine learning models are vulnerable to adversarial examples in their inputs, which has given rise to a field of research known as adversarial machine learning. Potential adversarial attacks include methods of poisoning datasets by perturbing input samples to mislead machine learning models into producing undesirable results. While such perturbations are often subtle and imperceptible from the perspective of a human, they can greatly affect the performance of machine learning models. This paper presents two methods of verifying the visual fidelity of image-based datasets by using QR codes to detect perturbations in the data. In the first method, a verification string is stored for each image in a dataset. These verification strings can be used to determine whether or not an image in the dataset has been perturbed. In the second method, only a single verification string is stored and can be used to verify whether an entire dataset is intact." @default.
- W3087932236 created "2020-10-01" @default.
- W3087932236 creator A5025592561 @default.
- W3087932236 creator A5032754540 @default.
- W3087932236 creator A5033444073 @default.
- W3087932236 creator A5042022850 @default.
- W3087932236 creator A5054741725 @default.
- W3087932236 creator A5068576783 @default.
- W3087932236 creator A5088366326 @default.
- W3087932236 date "2021-01-01" @default.
- W3087932236 modified "2023-10-17" @default.
- W3087932236 title "Utilizing QR codes to verify the visual fidelity of image datasets for machine learning" @default.
- W3087932236 cites W2018954508 @default.
- W3087932236 cites W2026503049 @default.
- W3087932236 cites W2132984323 @default.
- W3087932236 cites W2182452287 @default.
- W3087932236 cites W2206629542 @default.
- W3087932236 cites W2498755361 @default.
- W3087932236 cites W2609388470 @default.
- W3087932236 cites W2795884248 @default.
- W3087932236 cites W2896660479 @default.
- W3087932236 cites W2962700793 @default.
- W3087932236 cites W2969249185 @default.
- W3087932236 cites W2996806689 @default.
- W3087932236 cites W4247200422 @default.
- W3087932236 doi "https://doi.org/10.1016/j.jnca.2020.102834" @default.
- W3087932236 hasPublicationYear "2021" @default.
- W3087932236 type Work @default.
- W3087932236 sameAs 3087932236 @default.
- W3087932236 citedByCount "5" @default.
- W3087932236 countsByYear W30879322362021 @default.
- W3087932236 countsByYear W30879322362022 @default.
- W3087932236 crossrefType "journal-article" @default.
- W3087932236 hasAuthorship W3087932236A5025592561 @default.
- W3087932236 hasAuthorship W3087932236A5032754540 @default.
- W3087932236 hasAuthorship W3087932236A5033444073 @default.
- W3087932236 hasAuthorship W3087932236A5042022850 @default.
- W3087932236 hasAuthorship W3087932236A5054741725 @default.
- W3087932236 hasAuthorship W3087932236A5068576783 @default.
- W3087932236 hasAuthorship W3087932236A5088366326 @default.
- W3087932236 hasBestOaLocation W30879322362 @default.
- W3087932236 hasConcept C115961682 @default.
- W3087932236 hasConcept C119857082 @default.
- W3087932236 hasConcept C121332964 @default.
- W3087932236 hasConcept C12713177 @default.
- W3087932236 hasConcept C154945302 @default.
- W3087932236 hasConcept C157486923 @default.
- W3087932236 hasConcept C202444582 @default.
- W3087932236 hasConcept C2776459999 @default.
- W3087932236 hasConcept C33923547 @default.
- W3087932236 hasConcept C37736160 @default.
- W3087932236 hasConcept C41008148 @default.
- W3087932236 hasConcept C62520636 @default.
- W3087932236 hasConcept C76155785 @default.
- W3087932236 hasConcept C9652623 @default.
- W3087932236 hasConceptScore W3087932236C115961682 @default.
- W3087932236 hasConceptScore W3087932236C119857082 @default.
- W3087932236 hasConceptScore W3087932236C121332964 @default.
- W3087932236 hasConceptScore W3087932236C12713177 @default.
- W3087932236 hasConceptScore W3087932236C154945302 @default.
- W3087932236 hasConceptScore W3087932236C157486923 @default.
- W3087932236 hasConceptScore W3087932236C202444582 @default.
- W3087932236 hasConceptScore W3087932236C2776459999 @default.
- W3087932236 hasConceptScore W3087932236C33923547 @default.
- W3087932236 hasConceptScore W3087932236C37736160 @default.
- W3087932236 hasConceptScore W3087932236C41008148 @default.
- W3087932236 hasConceptScore W3087932236C62520636 @default.
- W3087932236 hasConceptScore W3087932236C76155785 @default.
- W3087932236 hasConceptScore W3087932236C9652623 @default.
- W3087932236 hasFunder F4320321001 @default.
- W3087932236 hasLocation W30879322361 @default.
- W3087932236 hasLocation W30879322362 @default.
- W3087932236 hasOpenAccess W3087932236 @default.
- W3087932236 hasPrimaryLocation W30879322361 @default.
- W3087932236 hasRelatedWork W2379758047 @default.
- W3087932236 hasRelatedWork W2903917280 @default.
- W3087932236 hasRelatedWork W2947659462 @default.
- W3087932236 hasRelatedWork W2961085424 @default.
- W3087932236 hasRelatedWork W3046843850 @default.
- W3087932236 hasRelatedWork W4220812973 @default.
- W3087932236 hasRelatedWork W4306674287 @default.
- W3087932236 hasRelatedWork W4312149667 @default.
- W3087932236 hasRelatedWork W4386716251 @default.
- W3087932236 hasRelatedWork W4224009465 @default.
- W3087932236 hasVolume "173" @default.
- W3087932236 isParatext "false" @default.
- W3087932236 isRetracted "false" @default.
- W3087932236 magId "3087932236" @default.
- W3087932236 workType "article" @default.