{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T03:00:50Z","timestamp":1730343650390,"version":"3.28.0"},"reference-count":17,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,1,24]]},"DOI":"10.23919\/eusipco47968.2020.9287700","type":"proceedings-article","created":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T21:54:18Z","timestamp":1608328458000},"page":"1-5","source":"Crossref","is-referenced-by-count":0,"title":["Hodge and Podge: Hybrid Supervised Sound Event Detection with Multi-Hot MixMatch and Composition Consistence Training"],"prefix":"10.23919","author":[{"given":"Ziqiang","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rujie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"mixup: Beyond empirical risk minimization","year":"2017","author":"zhang","key":"ref10"},{"article-title":"Mixmatch: A holistic approach to semi-supervised learning","year":"2019","author":"berthelot","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952261"},{"key":"ref13","article-title":"Freesound datasets: a platform for the creation of open audio datasets","author":"fonseca","year":"2017","journal-title":"Hu X Cunningham SJ Turnbull D Duan Z editors Proceedings of the 18th ISMIR Conference 2017 oct 23-27 Suzhou China [Canada] International Society for Music Information Retrieval 2017 p 486-93"},{"key":"ref14","first-page":"32","article-title":"The sins database for detection of daily activities in a home environment using an acoustic sensor network","author":"dekkers","year":"2017","journal-title":"Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017) Munich Germany"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/app6060162"},{"year":"2019","key":"ref16","article-title":"Detection and classification of acoustic scenes and events (dcase 2019) challenge task 4 results"},{"article-title":"Interpo-lation consistency training for semi-supervised learning","year":"2019","author":"verma","key":"ref17"},{"key":"ref4","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"tarvainen","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.33682\/006b-jx26"},{"key":"ref6","article-title":"Large-scale weakly labeled semi-supervised sound event detection in domestic environments","author":"serizel","year":"2018","journal-title":"Workshop on Detection and Classification of Acoustic Scenes and Events"},{"key":"ref5","article-title":"Mean teacher convolution system for dcase 2018 task 4","author":"lu","year":"2018","journal-title":"Tech Rep DCASE2016 Challenge"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.33682\/9kcj-bq06"},{"article-title":"Dcase 2018 challenge baseline with convolutional neural networks","year":"2018","author":"kong","key":"ref7"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1109\/TNN.2009.2015974","article-title":"Semi-supervised learning","volume":"20","author":"chapelle","year":"2009","journal-title":"IEEE Transactions on Neural Networks"},{"key":"ref1","article-title":"Semi-supervised learning literature survey","author":"zhu","year":"2005","journal-title":"University of Wisconsin-Madison Computer Sciences Department Tech Report"},{"key":"ref9","first-page":"7132","article-title":"Squeeze-and-excitation networks","author":"hu","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"}],"event":{"name":"2020 28th European Signal Processing Conference (EUSIPCO)","start":{"date-parts":[[2021,1,18]]},"location":"Amsterdam, Netherlands","end":{"date-parts":[[2021,1,21]]}},"container-title":["2020 28th European Signal Processing Conference (EUSIPCO)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9287308\/9287310\/09287700.pdf?arnumber=9287700","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,23]],"date-time":"2021-02-23T03:14:39Z","timestamp":1614050079000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9287700\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,24]]},"references-count":17,"URL":"https:\/\/doi.org\/10.23919\/eusipco47968.2020.9287700","relation":{},"subject":[],"published":{"date-parts":[[2021,1,24]]}}}