Matches in SemOpenAlex for { <https://semopenalex.org/work/W2976753843> ?p ?o ?g. }
- W2976753843 abstract "Machine learning is driven by data, yet while their availability is constantly increasing, training data require laborious, time consuming and error-prone labelling or ground truth acquisition, which in some cases is very difficult or even impossible. Recent works have resorted to synthetic data generation, but the inferior performance of models trained on synthetic data when applied to the real world, introduced the challenge of unsupervised domain adaptation. In this work we investigate an unsupervised domain adaptation technique that descends from another perspective, in order to avoid the complexity of adversarial training and cycle consistencies. We exploit the recent advances in photorealistic style transfer and take a fully data driven approach. While this concept is already implicitly formulated within the intricate objectives of domain adaptation GANs, we take an explicit approach and apply it directly as data pre-processing. The resulting technique is scalable, efficient and easy to implement, offers competitive performance to the complex state-of-the-art alternatives and can open up new pathways for domain adaptation." @default.
- W2976753843 created "2019-10-03" @default.
- W2976753843 creator A5021461498 @default.
- W2976753843 creator A5036173970 @default.
- W2976753843 creator A5059708050 @default.
- W2976753843 creator A5071585254 @default.
- W2976753843 creator A5071768096 @default.
- W2976753843 date "2019-09-24" @default.
- W2976753843 modified "2023-09-27" @default.
- W2976753843 title "Restyling Data: Application to Unsupervised Domain Adaptation." @default.
- W2976753843 cites W1722318740 @default.
- W2976753843 cites W1731081199 @default.
- W2976753843 cites W1903029394 @default.
- W2976753843 cites W1921093919 @default.
- W2976753843 cites W2012187833 @default.
- W2976753843 cites W2031342017 @default.
- W2976753843 cites W2095705004 @default.
- W2976753843 cites W2099471712 @default.
- W2976753843 cites W2108598243 @default.
- W2976753843 cites W2112796928 @default.
- W2976753843 cites W2160398734 @default.
- W2976753843 cites W2194775991 @default.
- W2976753843 cites W2271840356 @default.
- W2976753843 cites W2331143823 @default.
- W2976753843 cites W2340897893 @default.
- W2976753843 cites W2397830550 @default.
- W2976753843 cites W2412782625 @default.
- W2976753843 cites W2431874326 @default.
- W2976753843 cites W2487365028 @default.
- W2976753843 cites W2557465155 @default.
- W2976753843 cites W2558580397 @default.
- W2976753843 cites W2562192638 @default.
- W2976753843 cites W2584009249 @default.
- W2976753843 cites W2586114507 @default.
- W2976753843 cites W2755286543 @default.
- W2976753843 cites W2781228439 @default.
- W2976753843 cites W2781604162 @default.
- W2976753843 cites W2791763440 @default.
- W2976753843 cites W2795889831 @default.
- W2976753843 cites W2798414551 @default.
- W2976753843 cites W2883505290 @default.
- W2976753843 cites W2889900721 @default.
- W2976753843 cites W2895281799 @default.
- W2976753843 cites W2899771611 @default.
- W2976753843 cites W2907905507 @default.
- W2976753843 cites W2949667497 @default.
- W2976753843 cites W2949907962 @default.
- W2976753843 cites W2962793481 @default.
- W2976753843 cites W2962808524 @default.
- W2976753843 cites W2962835968 @default.
- W2976753843 cites W2963027561 @default.
- W2976753843 cites W2963073614 @default.
- W2976753843 cites W2963107255 @default.
- W2976753843 cites W2963120918 @default.
- W2976753843 cites W2963403405 @default.
- W2976753843 cites W2963446712 @default.
- W2976753843 cites W2963784072 @default.
- W2976753843 cites W2963826681 @default.
- W2976753843 cites W2964139811 @default.
- W2976753843 cites W2964339842 @default.
- W2976753843 cites W2968424372 @default.
- W2976753843 cites W2963459876 @default.
- W2976753843 hasPublicationYear "2019" @default.
- W2976753843 type Work @default.
- W2976753843 sameAs 2976753843 @default.
- W2976753843 citedByCount "0" @default.
- W2976753843 crossrefType "posted-content" @default.
- W2976753843 hasAuthorship W2976753843A5021461498 @default.
- W2976753843 hasAuthorship W2976753843A5036173970 @default.
- W2976753843 hasAuthorship W2976753843A5059708050 @default.
- W2976753843 hasAuthorship W2976753843A5071585254 @default.
- W2976753843 hasAuthorship W2976753843A5071768096 @default.
- W2976753843 hasConcept C119857082 @default.
- W2976753843 hasConcept C120665830 @default.
- W2976753843 hasConcept C121332964 @default.
- W2976753843 hasConcept C12713177 @default.
- W2976753843 hasConcept C134306372 @default.
- W2976753843 hasConcept C139807058 @default.
- W2976753843 hasConcept C154945302 @default.
- W2976753843 hasConcept C160920958 @default.
- W2976753843 hasConcept C165696696 @default.
- W2976753843 hasConcept C2776434776 @default.
- W2976753843 hasConcept C33923547 @default.
- W2976753843 hasConcept C36503486 @default.
- W2976753843 hasConcept C38652104 @default.
- W2976753843 hasConcept C41008148 @default.
- W2976753843 hasConcept C48044578 @default.
- W2976753843 hasConcept C77088390 @default.
- W2976753843 hasConcept C95623464 @default.
- W2976753843 hasConceptScore W2976753843C119857082 @default.
- W2976753843 hasConceptScore W2976753843C120665830 @default.
- W2976753843 hasConceptScore W2976753843C121332964 @default.
- W2976753843 hasConceptScore W2976753843C12713177 @default.
- W2976753843 hasConceptScore W2976753843C134306372 @default.
- W2976753843 hasConceptScore W2976753843C139807058 @default.
- W2976753843 hasConceptScore W2976753843C154945302 @default.
- W2976753843 hasConceptScore W2976753843C160920958 @default.
- W2976753843 hasConceptScore W2976753843C165696696 @default.
- W2976753843 hasConceptScore W2976753843C2776434776 @default.
- W2976753843 hasConceptScore W2976753843C33923547 @default.