{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:47:16Z","timestamp":1785890836362,"version":"3.56.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100002837","name":"Chang'an University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002837","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013290","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2020YFC1512000"],"award-info":[{"award-number":["2020YFC1512000"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61801332"],"award-info":[{"award-number":["61801332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/jstars.2021.3109237","type":"journal-article","created":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T20:22:48Z","timestamp":1631305368000},"page":"10091-10100","source":"Crossref","is-referenced-by-count":26,"title":["Scale-Robust Deep-Supervision Network for Mapping Building Footprints From High-Resolution Remote Sensing Images"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3778-2793","authenticated-orcid":false,"given":"Haonan","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0957-4628","authenticated-orcid":false,"given":"Xin","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengkun","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0059-8458","authenticated-orcid":false,"given":"Bo","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6890-3650","authenticated-orcid":false,"given":"Liangpei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"PyTorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019"},{"key":"ref38","article-title":"Machine learning for aerial image labeling","author":"volodymyr","year":"2013"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3041646"},{"key":"ref32","article-title":"Building footprint extraction from high-resolution images via spatial residual inception convolutional neural network","volume":"11","author":"liu","year":"2019","journal-title":"Remote Sens"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3026051"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00584"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2858817"},{"key":"ref36","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-24574-4_28","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2954461"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3022410"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2011.2168195"},{"key":"ref40","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2013.09.004"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3014312"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3070909"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3091758"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3018879"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3045273"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2907932"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.2991391"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/rs11030227"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2021.112589"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3004263"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3085870"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1080\/01431160304987"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/rs10091350"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.12.009"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2017.2669217"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2005.1525421"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/rs11070830"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.14358\/PERS.77.7.721"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.11.004"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.3017934"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/rs10071135"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2018.2849363"},{"key":"ref42","article-title":"SegNet: A deep convolutional encoder-decoder architecture for image segmentation","author":"badrinarayanan","year":"2016"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/rs11202380"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2019.2947473"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/rs10010144"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2016.2540798"},{"key":"ref43","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-01234-2_49","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"chen","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2020.2986380"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4609443\/9314330\/09535260.pdf?arnumber=9535260","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:56:55Z","timestamp":1639771015000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9535260\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/jstars.2021.3109237","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"value":"1939-1404","type":"print"},{"value":"2151-1535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}