{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T11:41:10Z","timestamp":1783078870811,"version":"3.54.6"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFA0702501"],"award-info":[{"award-number":["2018YFA0702501"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41974126"],"award-info":[{"award-number":["41974126"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41674116"],"award-info":[{"award-number":["41674116"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC Youth Science Foundation Project","doi-asserted-by":"publisher","award":["42104117"],"award-info":[{"award-number":["42104117"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tgrs.2023.3288737","type":"journal-article","created":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T01:25:36Z","timestamp":1687569936000},"page":"1-11","source":"Crossref","is-referenced-by-count":13,"title":["Seismic Stratigraphic Interpretation Based on Deep Active Learning"],"prefix":"10.1109","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5692-4101","authenticated-orcid":false,"given":"Xiaofeng","family":"Gu","sequence":"first","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0249-2144","authenticated-orcid":false,"given":"Wenkai","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0274-7477","authenticated-orcid":false,"given":"Yile","family":"Ao","sequence":"additional","affiliation":[{"name":"Machine Intelligent Sensing and Advanced Computing Lab, College of Electrical and Mechanical Engineering, Beijing University of Chemical Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1819-4678","authenticated-orcid":false,"given":"Yinshuo","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2401-2084","authenticated-orcid":false,"given":"Cao","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1190\/1.1437077"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2020.2991775"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1190\/geo2019-0413.1"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1190\/segam2013-0296.1"},{"key":"ref31","author":"alaudah","year":"2019","journal-title":"Facies classification benchmarK (1 0) [Data set]"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093363"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1190\/1.1444415"},{"key":"ref33","first-page":"8024","article-title":"PyTorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/0898-1221(82)90009-8"},{"key":"ref32","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1190\/segam2018-2996783.1"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.20948\/graphicon-2021-3027-564-570"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1190\/INT-2018-0249.1"},{"key":"ref16","first-page":"1","author":"chevitarese","year":"2018","journal-title":"Deep Learning Applied to Seismic Facies Classification A Methodology for Training"},{"key":"ref19","article-title":"Active learning literature survey","author":"settles","year":"2009"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7762543"},{"key":"ref24","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"xie","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref23","first-page":"1","article-title":"Contrastive clustering","author":"li","year":"2020","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref26","first-page":"9861","article-title":"DeepDPM: Deep clustering with an unknown number of clusters","author":"ronen","year":"2023","journal-title":"Proc IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/243"},{"key":"ref20","first-page":"1","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109817"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.313"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","first-page":"3","article-title":"UNet++: A nested U-Net architecture for medical image segmentation","author":"zhou","year":"2018","journal-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support"},{"key":"ref29","first-page":"370","article-title":"Usingdynamictimewarping tofindpatternsinsequences","volume":"359","author":"berndtd","year":"1994","journal-title":"Proc Work Notes Knowl Discovery Databases Workshop"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_46"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s11770-022-0924-8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3171694"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11004-020-09916-8"},{"key":"ref3","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Medical Image Computing and Computer-Assisted Intervention&#x2014;MICCAI"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1190\/geo2019-0433.1"},{"key":"ref5","article-title":"Semantic segmentation of seismic images","author":"civitarese","year":"2019","journal-title":"arXiv 1905 04307"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/10006360\/10159420.pdf?arnumber=10159420","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T17:32:30Z","timestamp":1690824750000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10159420\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2023.3288737","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}