{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T16:14:11Z","timestamp":1792080851944,"version":"4.4.0"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/waspaa.2019.8937231","type":"proceedings-article","created":{"date-parts":[[2019,12,24]],"date-time":"2019-12-24T06:50:13Z","timestamp":1577170213000},"page":"259-263","source":"Crossref","is-referenced-by-count":33,"title":["Unsupervised Adversarial Domain Adaptation Based on The Wasserstein Distance For Acoustic Scene Classification"],"prefix":"10.1109","author":[{"given":"Konstantinos","family":"Drossos","sequence":"first","affiliation":[{"name":"Tampere University,Audio Research Group,Tampere,Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Magron","sequence":"additional","affiliation":[{"name":"Tampere University,Audio Research Group,Tampere,Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tuomas","family":"Virtanen","sequence":"additional","affiliation":[{"name":"Tampere University,Audio Research Group,Tampere,Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1007\/978-3-319-24947-6_42","article-title":"A deeper look at dataset bias","volume":"9358","author":"tommasi","year":"2015","journal-title":"German Conference on Pattern Recognition"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref13","first-page":"8559","article-title":"Adversarial multiple source domain adaptation","author":"zhao","year":"2018","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref14","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v32i1.11767","article-title":"Multi-adversarial domain adaptation","author":"pei","year":"2018","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"ref15","first-page":"1989","article-title":"CyCADA: Cycle-consistent adversarial domain adaptation","volume":"80","author":"hoffman","year":"2018","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref16","article-title":"Improving adversarial discriminative domain adaptation","author":"chadha","year":"2018","journal-title":"CoRR"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1007\/978-3-319-71246-8_45","article-title":"Theoretical analysis of domain adaptation with optimal transport","author":"redko","year":"2017","journal-title":"Machine Learning and Knowledge Discovery in Databases"},{"key":"ref18","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume":"70","author":"arjovsky","year":"2017","journal-title":"Proceedings of the 34th International Conference on Machine Learning"},{"key":"ref19","article-title":"Adversarial unsupervised domain adaptation for acoustic scene classification","author":"gharib","year":"2018"},{"key":"ref4","article-title":"Acoustic scene classification with fully convolutional neural networks and I-vectors","author":"dorfer","year":"2018","journal-title":"DCASE2018 Challenge"},{"key":"ref3","article-title":"Acoustic scene classification by ensemble of spectrograms based on adaptive temporal divisions","author":"sakashita","year":"2018","journal-title":"DCASE2018 Challenge"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1007\/978-3-540-87987-9_8","article-title":"Sample selection bias correction theory","author":"cortes","year":"2008","journal-title":"Algorithmic Learning Theory"},{"key":"ref5","first-page":"138","article-title":"Unsupervised adversarial domain adaptation for acoustic scene classification","author":"gharib","year":"2018","journal-title":"Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995347"},{"key":"ref7","first-page":"2096","article-title":"Domain- adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"The Journal of Machine Learning Research"},{"key":"ref2","article-title":"Acoustic scene classification using deep convolutional neural network and multiple spectrograms fusion","author":"weiping","year":"2017","journal-title":"Dcase2016 challenge"},{"key":"ref9","first-page":"131","author":"gretton","year":"2009","journal-title":"Covariate shift and local learning by distribution matching"},{"key":"ref1","article-title":"Convolutional neural networks with binaural representations and background subtraction for acoustic scene classification","author":"han","year":"2017","journal-title":"Dcase2016 challenge"},{"key":"ref20","first-page":"129","article-title":"Learning bounds for domain adaptation","author":"blitzer","year":"2008","journal-title":"Advances in Neural Information Processing Systems 20"},{"key":"ref22","article-title":"Unsupervised domain adaptation by backpropagation","author":"ganin","year":"2015","journal-title":"Proceedings ofthe 32nd International Conference on Machine Learning (ICML)"},{"key":"ref21","author":"vapnik","year":"1999","journal-title":"The Nature of Statistical Learning Theory"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.exmath.2011.06.005"},{"key":"ref23","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27"},{"key":"ref26","article-title":"Automatic differentiation in PyTorch","author":"paszke","year":"2017","journal-title":"NIPS-W"},{"key":"ref25","article-title":"An overview of gradient descent optimization algorithms","author":"ruder","year":"2016","journal-title":"CoRR"}],"event":{"name":"2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","location":"New Paltz, NY, USA","start":{"date-parts":[[2019,10,20]]},"end":{"date-parts":[[2019,10,23]]}},"container-title":["2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8932990\/8937073\/08937231.pdf?arnumber=8937231","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T08:43:45Z","timestamp":1665305025000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8937231\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/waspaa.2019.8937231","relation":{},"subject":[],"published":{"date-parts":[[2019,10]]}}}