{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T16:02:03Z","timestamp":1730304123665,"version":"3.28.0"},"reference-count":29,"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.2019.8937249","type":"proceedings-article","created":{"date-parts":[[2019,12,24]],"date-time":"2019-12-24T06:50:13Z","timestamp":1577170213000},"page":"16-20","source":"Crossref","is-referenced-by-count":5,"title":["Model-Agnostic Approaches To Handling Noisy Labels When Training Sound Event Classifiers"],"prefix":"10.1109","author":[{"given":"Eduardo","family":"Fonseca","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frederic","family":"Font","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xavier","family":"Serra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"960","article-title":"Decoupling","author":"malach","year":"2017","journal-title":"when to update\" from\" how to update\" \" in Advances in Neural Information Processing Systems"},{"article-title":"Mentor-net: Learning data-driven curriculum for very deep neural networks on corrupted labels","year":"2017","author":"jiang","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.240"},{"article-title":"Training deep neural-networks using a noise adaptation layer","year":"2016","author":"goldberger","key":"ref13"},{"key":"ref14","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","author":"zhang","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.696"},{"article-title":"Learning sound events from webly labeled data","year":"2018","author":"kumar","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.33682\/w13e-5v06"},{"key":"ref18","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref4","article-title":"General-purpose tagging of freesound audio with audioset labels: task description, dataset, and baseline","author":"fonseca","year":"0","journal-title":"Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/WASPAA.2015.7336899"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952261"},{"key":"ref29","article-title":"Audio tagging system using densely connected convolutional networks","author":"jeong","year":"0","journal-title":"Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683158"},{"article-title":"Understanding deep learning requires rethinking generalization","year":"2016","author":"zhang","key":"ref8"},{"key":"ref7","first-page":"233","article-title":"A closer look at memorization in deep networks","author":"arpit","year":"0"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806390"},{"key":"ref9","first-page":"8527","article-title":"Co-teaching: Robust training of deep neural networks with extremely noisy labels","author":"han","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2655045"},{"journal-title":"Deep Learning","year":"2016","author":"goodfellow","key":"ref20"},{"key":"ref22","first-page":"1919","article-title":"Robust loss functions under label noise for deep neural networks","author":"ghosh","year":"2017","journal-title":"AAAI"},{"article-title":"mixup: Beyond empirical risk minimization","year":"2017","author":"zhang","key":"ref21"},{"key":"ref24","first-page":"486","article-title":"Freesound datasets: a platform for the creation of open audio datasets","author":"fonseca","year":"2017","journal-title":"Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR 2017)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502245"},{"article-title":"Adam: A method for stochastic optimization","year":"0","author":"kingma","key":"ref26"},{"key":"ref25","article-title":"A simple fusion of deep and shallow learning for acoustic scene classification","author":"fonseca","year":"2018","journal-title":"Proceedings of the 15th Sound & Music Computing Conference (SMC 2018)"}],"event":{"name":"2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","start":{"date-parts":[[2019,10,20]]},"location":"New Paltz, NY, USA","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\/08937249.pdf?arnumber=8937249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T03:12:18Z","timestamp":1657854738000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8937249\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/waspaa.2019.8937249","relation":{},"subject":[],"published":{"date-parts":[[2019,10]]}}}