{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T16:49:06Z","timestamp":1768409346298,"version":"3.49.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Science and Technology Major Project of Henan Province","award":["201400210900"],"award-info":[{"award-number":["201400210900"]}]},{"name":"National Supercomputing Center in Zhengzhou"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tgrs.2021.3128539","type":"journal-article","created":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T20:28:05Z","timestamp":1637094485000},"page":"1-18","source":"Crossref","is-referenced-by-count":9,"title":["Exploring Label Probability Sequence to Robustly Learn Deep Convolutional Neural Networks for Road Extraction With Noisy Datasets"],"prefix":"10.1109","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1077-8831","authenticated-orcid":false,"given":"Panle","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6694-0183","authenticated-orcid":false,"given":"Xiaohui","family":"He","sequence":"additional","affiliation":[{"name":"School of Geoscience and Technology and the Ecometeorology Joint Laboratory, Chinese Academy of Meteorological Science, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8919-8647","authenticated-orcid":false,"given":"Mengjia","family":"Qiao","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9963-4422","authenticated-orcid":false,"given":"Xijie","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Jiamian","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Xiaoyu","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Geoscience and Technology and the Ecometeorology Joint Laboratory, Chinese Academy of Meteorological Science, Zhengzhou University, Zhengzhou, China"}]},{"given":"Tao","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1050-4486","authenticated-orcid":false,"given":"Dingjun","family":"Song","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Mingyang","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7743-8893","authenticated-orcid":false,"given":"Disheng","family":"Miao","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Yinjie","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Zhihui","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Geoscience and Technology and the Ecometeorology Joint Laboratory, Chinese Academy of Meteorological Science, Zhengzhou University, Zhengzhou, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2870871"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00496"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2612821"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518711"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.11.010"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15567-3_16"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3041021.3054250"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2802944"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3281548.3281550"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00769"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3003425"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2669341"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2926397"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.08.019"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00041"},{"key":"ref17","first-page":"567","article-title":"Learning to label aerial images from noisy data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Mnih"},{"key":"ref18","article-title":"Training convolutional networks with noisy labels","volume-title":"arXiv:1406.2080","author":"Sukhbaatar","year":"2014"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2938215"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3023112"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2861992"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2896471"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2823866"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3001335"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2677468"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3068280"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3040879"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58568-6_3"},{"key":"ref29","first-page":"233","article-title":"A closer look at memorization in deep networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Arpit"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/rs12091444"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3016086"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2912301"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2719738"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2913079"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106771"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2292894"},{"key":"ref37","article-title":"Training deep neural-networks using a noise adaptation layer","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Goldberger"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10894"},{"key":"ref39","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","volume-title":"arXiv:1805.07836","author":"Zhang","year":"2018"},{"key":"ref40","article-title":"IMAE for noise-robust learning: Mean absolute error does not treat examples equally and gradient magnitude\u2019s variance matters","volume-title":"arXiv:1903.12141","author":"Wang","year":"2019"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3059088"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2875470"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/204"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2899045"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2659740"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.06.017"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2868748"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2989241"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.08.117"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.09.003"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.08.025"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24075-6_46"},{"issue":"7","key":"ref55","first-page":"2121","article-title":"Adaptive subgradient methods for online learning and stochastic optimization","volume":"12","author":"Duchi","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref56","article-title":"ADADELTA: An adaptive learning rate method","volume-title":"arXiv:1212.5701","author":"Zeiler","year":"2012"},{"key":"ref57","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv:1412.6980","author":"Kingma","year":"2014"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9633014\/09615159.pdf?arnumber=9615159","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T17:27:03Z","timestamp":1729618023000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9615159\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2021.3128539","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}