{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T17:19:17Z","timestamp":1775755157219,"version":"3.50.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"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":["61901376"],"award-info":[{"award-number":["61901376"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["G2019KY05301"],"award-info":[{"award-number":["G2019KY05301"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002663","name":"Peak Experience Plan in Northwestern Polytechnical University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1109\/tcsvt.2020.2995754","type":"journal-article","created":{"date-parts":[[2020,5,20]],"date-time":"2020-05-20T20:54:44Z","timestamp":1590008084000},"page":"1091-1102","source":"Crossref","is-referenced-by-count":257,"title":["Multi-Scale Metric Learning for Few-Shot Learning"],"prefix":"10.1109","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5429-2748","authenticated-orcid":false,"given":"Wen","family":"Jiang","sequence":"first","affiliation":[]},{"given":"Kai","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4858-823X","authenticated-orcid":false,"given":"Jie","family":"Geng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8181-7001","authenticated-orcid":false,"given":"Xinyang","family":"Deng","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8297117"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2771779"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-016-0634-8"},{"key":"ref31","article-title":"All you need is a good init","author":"mishkin","year":"2015","journal-title":"arXiv 1511 06422"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00534"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_59"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2808938"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2964679"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2913095"},{"key":"ref28","first-page":"1","article-title":"Meta-learning with latent embedding optimization","author":"rusu","year":"2019","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00049"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00294"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2953922"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803599"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451346"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2815559"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2910052"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_35"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.242"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref56","first-page":"1","article-title":"Learning to propagate labels: Transductive propagation network for few-shot learning","author":"liu","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref55","first-page":"3661","article-title":"Rapid adaptation with conditionally shifted neurons","author":"munkhdalai","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref54","article-title":"Meta-learning for semi-supervised few-shot classification","author":"ren","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref52","article-title":"Revisiting metric learning for few-shot image classification","author":"li","year":"2019","journal-title":"arXiv 1907 03123"},{"key":"ref10","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn (ICML)"},{"key":"ref11","first-page":"1","article-title":"Siamese neural networks for one-shot image recognition","volume":"2","author":"koch","year":"2015","journal-title":"Proc Int Conf Mach Learn Workshops (ICMLW)"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2017.01.012"},{"key":"ref12","first-page":"3630","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1023\/A:1019956318069"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.002"},{"key":"ref15","first-page":"357","article-title":"One-shot visual imitation learning via meta-learning","author":"finn","year":"2017","journal-title":"Proc Conf Rob Learn (CoRL)"},{"key":"ref16","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"finn","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn (ICML)"},{"key":"ref17","first-page":"1842","article-title":"Meta-learning with memory-augmented neural networks","author":"santoro","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.11.001"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2019.2918999"},{"key":"ref4","first-page":"4077","article-title":"Prototypical networks for few-shot learning","author":"snell","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5529-2_1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref5","first-page":"1","article-title":"Optimization as a model for few-shot learning","author":"ravi","year":"2016","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref49","first-page":"207","article-title":"Distance metric learning for large margin nearest neighbor classification","volume":"10","author":"weinberger","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/0010-0285(88)90014-X"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2666151"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_44"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186154"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2017.07.015"},{"key":"ref42","first-page":"9516","article-title":"Probabilistic model-agnostic meta-learning","author":"finn","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref41","first-page":"7332","article-title":"Bayesian model-agnostic meta-learning","author":"kim","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref44","first-page":"1","article-title":"A simple neural attentive meta-learner","author":"mishra","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref43","article-title":"Deep meta-learning: Learning to learn in the concept space","author":"zhou","year":"2018","journal-title":"arXiv 1802 03596"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/9370015\/09097252.pdf?arnumber=9097252","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:28Z","timestamp":1652194228000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9097252\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3]]},"references-count":57,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2020.2995754","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3]]}}}