{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:39:06Z","timestamp":1774449546778,"version":"3.50.1"},"reference-count":60,"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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62022063"],"award-info":[{"award-number":["62022063"]}],"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.2023.3291439","type":"journal-article","created":{"date-parts":[[2023,7,3]],"date-time":"2023-07-03T18:09:56Z","timestamp":1688407796000},"page":"1-16","source":"Crossref","is-referenced-by-count":8,"title":["Multiple-Instance Metric Learning Network for Hyperspectral Target Detection"],"prefix":"10.1109","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7234-9804","authenticated-orcid":false,"given":"Bo","family":"Yang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]},{"given":"Yi","family":"He","sequence":"additional","affiliation":[{"name":"Test Center, National University of Defense Technology, Xi&#x2019;an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1392-8348","authenticated-orcid":false,"given":"Changzhe","family":"Jiao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]},{"given":"Xiao","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]},{"given":"Guozhen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2329-1481","authenticated-orcid":false,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7501-0009","authenticated-orcid":false,"given":"Jinjian","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3140798"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2756632"},{"key":"ref56","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc Int Int Artif Intell Statist (AISTATS)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.08.012"},{"key":"ref59","article-title":"MUUFL Gulfport hyperspectral and LiDAR airborne data set","author":"gader","year":"2013"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS47720.2021.9553094"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3013022"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898420"},{"key":"ref52","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2406334"},{"key":"ref55","first-page":"1","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(96)00034-3"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2008.11.007"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3060966"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2900465"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.08.026"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3031902"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3210389"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3082289"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00877"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3104392"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICME46284.2020.9102722"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00190"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.145"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3084106"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_31"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.283"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00208"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2023.109016"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-38617-7_6"},{"key":"ref9","first-page":"1","article-title":"A framework for multiple-instance learning","volume":"10","author":"maron","year":"1997","journal-title":"Proc Adv Neural Inf Process Syst (NeurIPS)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2020.112129"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2022.03.014"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2013.2278992"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3141843"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3129483"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2975718"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15567-3_3"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.202"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01824"},{"key":"ref31","first-page":"1","article-title":"EM-DD: An improved multiple-instance learning technique","volume":"14","author":"zhang","year":"2001","journal-title":"Proc Adv Neural Inf Process Syst (NeurIPS)"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01628"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.248"},{"key":"ref32","first-page":"1","article-title":"Support vector machines for multiple-instance learning","volume":"15","author":"andrews","year":"2002","journal-title":"Proc Adv Neural Inf Process Syst (NeurIPS)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2020.111938"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3069716"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-29843-y"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2021.12.005"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01409"},{"key":"ref23","first-page":"2136","article-title":"TransMIL: Transformer based correlated multiple instance learning for whole slide image classification","volume":"34","author":"shao","year":"2021","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00529"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3056887"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.009"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3087662"},{"key":"ref21","first-page":"2127","article-title":"Attention-based deep multiple instance learning","author":"ilse","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.226"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01379"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3112011"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2008.4779144"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/10006360\/10171432.pdf?arnumber=10171432","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T18:10:44Z","timestamp":1691431844000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10171432\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":60,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2023.3291439","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}