{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T18:37:12Z","timestamp":1775759832786,"version":"3.50.1"},"reference-count":18,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.1109\/embc.2018.8513102","type":"proceedings-article","created":{"date-parts":[[2018,11,16]],"date-time":"2018-11-16T04:03:08Z","timestamp":1542340988000},"page":"4776-4779","source":"Crossref","is-referenced-by-count":28,"title":["Deep Unsupervised Representation Learning for Abnormal Heart Sound Classification"],"prefix":"10.1109","author":[{"given":"Shahin","family":"Amiriparian","sequence":"first","affiliation":[]},{"given":"Maximilian","family":"Schmitt","sequence":"additional","affiliation":[]},{"given":"Nicholas","family":"Cummins","sequence":"additional","affiliation":[]},{"given":"Kun","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Fengquan","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Bjorn","family":"Schuller","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"609","article-title":"Classification of normal\/abnormal heart sound recordings: The PhysioNet\/Computing in Cardiology Challenge 2016","author":"clifford","year":"2016","journal-title":"2016 Computing in Cardiology Conference (CinC)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2017.8037876"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6579\/aa7841"},{"key":"ref13","first-page":"581","article-title":"Can electrocardiogram classification be applied to phonocardiogram data? — An analysis using recurrent neural networks","author":"scholzel","year":"2016","journal-title":"2016 Computing in Cardiology Conference (CinC)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref15","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27"},{"key":"ref16","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"Journal of Machine Learning Research"},{"key":"ref17","first-page":"15","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502224"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2015.2437951"},{"key":"ref6","first-page":"17","article-title":"Sequence to sequence autoencoders for unsupervised representation learning from audio","author":"amiriparian","year":"2017","journal-title":"DCASE2017"},{"key":"ref5","first-page":"5","article-title":"openXBOW — Introducing the Passau open-source crossmodal bag-of-words toolkit","volume":"18","author":"schmitt","year":"2017","journal-title":"Journal of Machine Learning Research"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"148","DOI":"10.21437\/Interspeech.2013-56","article-title":"The INTERSPEECH 2013 computational paralinguistics challenge: Social signals, conflict, emotion, autism","author":"schuller","year":"2013","journal-title":"Proc of Interspeech"},{"key":"ref7","article-title":"audeep: Unsupervised learning of representations from audio with deep recurrent neural networks","author":"freitag","year":"2017","journal-title":"arXiv preprint arXiv 1712 04382"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1161\/CIR.0000000000000366","article-title":"Executive summary: Heart disease and stroke statistics-2016 update: A report from the american heart association","volume":"133","author":"mozaffarian","year":"2016","journal-title":"Circulation"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1088\/0967-3334\/37\/12\/2181"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"3442","DOI":"10.21437\/Interspeech.2017-43","article-title":"The INTERSPEECH 2017 Computational Paralinguistics Challenge: Addressee, Cold & Snoring","author":"schuller","year":"2017","journal-title":"Proc Interspeech 2017"}],"event":{"name":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","location":"Honolulu, HI","start":{"date-parts":[[2018,7,18]]},"end":{"date-parts":[[2018,7,21]]}},"container-title":["2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8471725\/8512178\/08513102.pdf?arnumber=8513102","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T12:36:08Z","timestamp":1720787768000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8513102\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/embc.2018.8513102","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}