FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2931508961> ?p ?o ?g. }

• W2931508961 abstract "One of the frontier issues that severely hamper the development of automatic snore sound classification (ASSC) associates to the lack of sufficient supervised training data. To cope with this problem, we propose a novel data augmentation approach based on semi-supervised conditional Generative Adversarial Networks (scGANs), which aims to automatically learn a mapping strategy from a random noise space to original data distribution. The proposed approach has the capability of well synthesizing 'realistic' high-dimensional data, while requiring no additional annotation process. To handle the mode collapse problem of GANs, we further introduce an ensemble strategy to enhance the diversity of the generated data. The systematic experiments conducted on a widely used Munich-Passau snore sound corpus demonstrate that the scGANs-based systems can remarkably outperform other classic data augmentation systems, and are also competitive to other recently reported systems for ASSC." @default.
• W2931508961 created "2019-04-11" @default.
• W2931508961 creator A5032971738 @default.
• W2931508961 creator A5036056631 @default.
• W2931508961 creator A5049646773 @default.
• W2931508961 creator A5052703085 @default.
• W2931508961 creator A5069921704 @default.
• W2931508961 creator A5084541916 @default.
• W2931508961 date "2019-03-29" @default.
• W2931508961 modified "2023-09-24" @default.
• W2931508961 title "Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data" @default.
• W2931508961 cites W1924770834 @default.
• W2931508961 cites W1933340426 @default.
• W2931508961 cites W1959608418 @default.
• W2931508961 cites W1975648706 @default.
• W2931508961 cites W1991165771 @default.
• W2931508961 cites W2026191693 @default.
• W2931508961 cites W2071879357 @default.
• W2931508961 cites W2085662862 @default.
• W2931508961 cites W2099471712 @default.
• W2931508961 cites W2125389028 @default.
• W2931508961 cites W2148143831 @default.
• W2931508961 cites W2193413348 @default.
• W2931508961 cites W2407080277 @default.
• W2931508961 cites W2412510955 @default.
• W2931508961 cites W2423557781 @default.
• W2931508961 cites W2432004435 @default.
• W2931508961 cites W2513507089 @default.
• W2931508961 cites W2538918575 @default.
• W2931508961 cites W2554314924 @default.
• W2931508961 cites W2558942501 @default.
• W2931508961 cites W2573380384 @default.
• W2931508961 cites W2600556233 @default.
• W2931508961 cites W2610961739 @default.
• W2931508961 cites W2621727638 @default.
• W2931508961 cites W2622385665 @default.
• W2931508961 cites W2740284003 @default.
• W2931508961 cites W2745435358 @default.
• W2931508961 cites W2747993267 @default.
• W2931508961 cites W2749046237 @default.
• W2931508961 cites W2749812777 @default.
• W2931508961 cites W2750268731 @default.
• W2931508961 cites W2755577605 @default.
• W2931508961 cites W2765811365 @default.
• W2931508961 cites W2767019926 @default.
• W2931508961 cites W2770173563 @default.
• W2931508961 cites W2774755175 @default.
• W2931508961 cites W2775795276 @default.
• W2931508961 cites W2789894922 @default.
• W2931508961 cites W2796733030 @default.
• W2931508961 cites W2888964888 @default.
• W2931508961 cites W2890002510 @default.
• W2931508961 cites W2892133643 @default.
• W2931508961 cites W2949888546 @default.
• W2931508961 cites W2950067852 @default.
• W2931508961 cites W2953318193 @default.
• W2931508961 cites W2962686539 @default.
• W2931508961 cites W2963614358 @default.
• W2931508961 cites W2963684088 @default.
• W2931508961 cites W2963709863 @default.
• W2931508961 cites W2964229681 @default.
• W2931508961 cites W2964268978 @default.
• W2931508961 doi "https://doi.org/10.48550/arxiv.1903.12422" @default.
• W2931508961 hasPublicationYear "2019" @default.
• W2931508961 type Work @default.
• W2931508961 sameAs 2931508961 @default.
• W2931508961 citedByCount "1" @default.
• W2931508961 countsByYear W29315089612021 @default.
• W2931508961 crossrefType "posted-content" @default.
• W2931508961 hasAuthorship W2931508961A5032971738 @default.
• W2931508961 hasAuthorship W2931508961A5036056631 @default.
• W2931508961 hasAuthorship W2931508961A5049646773 @default.
• W2931508961 hasAuthorship W2931508961A5052703085 @default.
• W2931508961 hasAuthorship W2931508961A5069921704 @default.
• W2931508961 hasAuthorship W2931508961A5084541916 @default.
• W2931508961 hasBestOaLocation W29315089611 @default.
• W2931508961 hasConcept C111919701 @default.
• W2931508961 hasConcept C115961682 @default.
• W2931508961 hasConcept C119857082 @default.
• W2931508961 hasConcept C154945302 @default.
• W2931508961 hasConcept C2776321320 @default.
• W2931508961 hasConcept C39890363 @default.
• W2931508961 hasConcept C41008148 @default.
• W2931508961 hasConcept C98045186 @default.
• W2931508961 hasConcept C99498987 @default.
• W2931508961 hasConceptScore W2931508961C111919701 @default.
• W2931508961 hasConceptScore W2931508961C115961682 @default.
• W2931508961 hasConceptScore W2931508961C119857082 @default.
• W2931508961 hasConceptScore W2931508961C154945302 @default.
• W2931508961 hasConceptScore W2931508961C2776321320 @default.
• W2931508961 hasConceptScore W2931508961C39890363 @default.
• W2931508961 hasConceptScore W2931508961C41008148 @default.
• W2931508961 hasConceptScore W2931508961C98045186 @default.
• W2931508961 hasConceptScore W2931508961C99498987 @default.
• W2931508961 hasLocation W29315089611 @default.
• W2931508961 hasLocation W29315089612 @default.
• W2931508961 hasLocation W29315089613 @default.
• W2931508961 hasOpenAccess W2931508961 @default.
• W2931508961 hasPrimaryLocation W29315089611 @default.
• W2931508961 hasRelatedWork W151193258 @default.

• next