{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T21:13:19Z","timestamp":1776114799953,"version":"3.50.1"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T00:00:00Z","timestamp":1666569600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T00:00:00Z","timestamp":1666569600000},"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":[[2022,10,24]]},"DOI":"10.1109\/sibgrapi55357.2022.9991791","type":"proceedings-article","created":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T19:42:48Z","timestamp":1672083768000},"page":"25-30","source":"Crossref","is-referenced-by-count":7,"title":["A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels"],"prefix":"10.1109","author":[{"given":"Emeson","family":"Pereira","sequence":"first","affiliation":[{"name":"Universidade Federal Rural de Pernambuco,PPGIA,Department of Computing,Recife,Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gustavo","family":"Carneiro","sequence":"additional","affiliation":[{"name":"Australian Institute of Machine Learning University of Adelaide,School of Computer Science,Adelaide,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Filipe R.","family":"Cordeiro","sequence":"additional","affiliation":[{"name":"Universidade Federal Rural de Pernambuco,Visual Computing Lab,Recife,Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3084827"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSAI.2018.8599448"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106771"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-020-09825-6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI51738.2020.00010"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00793"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7687-1_79"},{"key":"ref10","article-title":"Dividemix: Learning with noisy labels as semi-supervised learning","author":"Li","year":"2020","journal-title":"arXiv preprint arXiv:2002.07394"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref13","article-title":"Imae for noise-robust learning: Mean absolute error does not treat examples equally and gradient magnitude\u2019s variance matters","author":"Wang","year":"2019","journal-title":"arXiv preprint arXiv:1903.12141"},{"key":"ref14","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":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00058"},{"key":"ref16","volume-title":"Pumpout: A meta approach for robustly training deep neural networks with noisy labels","author":"Han","year":"2018"},{"key":"ref17","article-title":"Propmix: Hard sample filtering and proportional mixup for learning with noisy labels","author":"Cordeiro","year":"2021","journal-title":"arXiv preprint arXiv:2110.11809"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00931"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i13.17364"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.240"},{"key":"ref23","article-title":"Improved regularization of convolutional neural networks with cutout","author":"DeVries","year":"2017","journal-title":"arXiv preprint arXiv:1708.04552"},{"key":"ref24","article-title":"Augmix: A simple data processing method to improve robustness and uncertainty","author":"Hendrycks","year":"2019","journal-title":"arXiv preprint arXiv:1912.02781"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref26","volume-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298885"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_38"}],"event":{"name":"2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","location":"Natal, Brazil","start":{"date-parts":[[2022,10,24]]},"end":{"date-parts":[[2022,10,27]]}},"container-title":["2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9991741\/9991742\/09991791.pdf?arnumber=9991791","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T12:05:21Z","timestamp":1706789121000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9991791\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,24]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/sibgrapi55357.2022.9991791","relation":{},"subject":[],"published":{"date-parts":[[2022,10,24]]}}}