{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T16:52:52Z","timestamp":1783788772641,"version":"3.55.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872379"],"award-info":[{"award-number":["61872379"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701508"],"award-info":[{"award-number":["61701508"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61372163"],"award-info":[{"award-number":["61372163"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906206"],"award-info":[{"award-number":["61906206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71701205"],"award-info":[{"award-number":["71701205"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of\u00a0Hunan Province","doi-asserted-by":"publisher","award":["2018JJ3613"],"award-info":[{"award-number":["2018JJ3613"]}],"id":[{"id":"10.13039\/501100004735","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":[[2020]]},"DOI":"10.1109\/jstars.2020.2995703","type":"journal-article","created":{"date-parts":[[2020,5,28]],"date-time":"2020-05-28T16:30:55Z","timestamp":1590683455000},"page":"2778-2792","source":"Crossref","is-referenced-by-count":43,"title":["A Class Imbalance Loss for Imbalanced Object Recognition"],"prefix":"10.1109","volume":"13","author":[{"given":"Linbin","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0321-9900","authenticated-orcid":false,"given":"Caiguang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6908-1975","authenticated-orcid":false,"given":"Sinong","family":"Quan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4524-2698","authenticated-orcid":false,"given":"Huaxin","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gangyao","family":"Kuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2011-2873","authenticated-orcid":false,"given":"Li","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2692524"},{"key":"ref33","article-title":"Batch-normalized maxout network in network","author":"chang","year":"0","journal-title":"CoRR"},{"key":"ref32","first-page":"464","article-title":"Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree","author":"lee","year":"0","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref31","first-page":"562","article-title":"Deeply-supervised nets","author":"lee","year":"0","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2551720"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2014.2332076"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2015.2436694"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2011.2162526"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2012.2210385"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299170"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8519123"},{"key":"ref29","article-title":"Convolutional networks for images, speech, and time series","author":"lecun","year":"1998","journal-title":"The Handbook of Brain Theory and Neural Networks"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0192-5"},{"key":"ref20","first-page":"21","article-title":"SSD: Single shot multibox detector","author":"liu","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296411"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.5194\/isprsarchives-XLI-B7-423-2016"},{"key":"ref50","first-page":"3637","article-title":"Matching networks for one shot learning","author":"vinyals","year":"0","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref51","first-page":"4077","article-title":"Prototypical networks for few-shot learning","author":"snell","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref55","first-page":"807","article-title":"Rectified linear units improve restricted Boltzmann machines","author":"nair","year":"0","journal-title":"Proc 27th Int Conf Mach Learn"},{"key":"ref54","article-title":"Meta-dataset: A dataset of datasets for learning to learn from few examples","author":"triantafillou","year":"0","journal-title":"Proc Intl Conf on Learning Representations"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref52","first-page":"2568","article-title":"One shot learning of simple visual concepts","volume":"33","author":"lake","year":"2011","journal-title":"Cogn Sci"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00264"},{"key":"ref40","first-page":"878","article-title":"Borderline-smote: A new over-sampling method in imbalanced data sets learning","author":"han","year":"0","journal-title":"Proc Int Conf Intell Comput"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2914680"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref14","first-page":"1583","article-title":"Multiset feature learning for highly imbalanced data classification","author":"wu","year":"0","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2832629"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.fss.2007.12.023"},{"key":"ref17","article-title":"Optimization as a model for few-shot learning","author":"ravi","year":"0","journal-title":"Proc of the Int Conf on Learning Representations (ICLR)"},{"key":"ref18","article-title":"R2CNN: Rotational region CNN for orientation robust scene text detection","author":"jiang","year":"2017","journal-title":"arXiv 1706 09579"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00644"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-012-0178-0"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2008.239"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00800"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.259"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01247-4"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref49","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"finn","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1109\/TNNLS.2017.2732482","article-title":"Cost-sensitive learning of deep feature representations from imbalanced data","volume":"29","author":"khan","year":"2018","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref45","first-page":"1842","article-title":"Meta-learning with memory-augmented neural networks","author":"santoro","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1109\/TSMCB.2008.2007853","article-title":"Exploratory undersampling for class-imbalance learning","volume":"39","author":"liu","year":"2009","journal-title":"IEEE Trans Syst Man Cybern B Cybern"},{"key":"ref47","article-title":"TensorFlow: Large-scale machine learning on heterogeneous distributed systems","volume":"39","author":"girija","year":"2016","journal-title":"software available from tensorflow org"},{"key":"ref42","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01307-2_43"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00610"},{"key":"ref43","first-page":"2104","article-title":"One-shot unsupervised cross domain translation","author":"benaim","year":"0","journal-title":"Proc Int Conf Neural Inf Process"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4609443\/8994817\/09103243.pdf?arnumber=9103243","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:30:09Z","timestamp":1641987009000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9103243\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/jstars.2020.2995703","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"value":"1939-1404","type":"print"},{"value":"2151-1535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}