{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T14:51:37Z","timestamp":1773931897903,"version":"3.50.1"},"reference-count":78,"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\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["CSC202006280327"],"award-info":[{"award-number":["CSC202006280327"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010428","name":"Innovation and Technology Fund","doi-asserted-by":"publisher","award":["PRP\/009\/22FX"],"award-info":[{"award-number":["PRP\/009\/22FX"]}],"id":[{"id":"10.13039\/501100010428","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016909","name":"Microsoft Research Asia Fund","doi-asserted-by":"publisher","award":["P0040568"],"award-info":[{"award-number":["P0040568"]}],"id":[{"id":"10.13039\/100016909","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["20232BAB212025"],"award-info":[{"award-number":["20232BAB212025"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]},{"name":"High-level and Urgently Needed Overseas Talent Programs of Jiangxi Province","award":["20232BCJ25024"],"award-info":[{"award-number":["20232BCJ25024"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tifs.2023.3309458","type":"journal-article","created":{"date-parts":[[2023,8,28]],"date-time":"2023-08-28T17:51:49Z","timestamp":1693245109000},"page":"5431-5446","source":"Crossref","is-referenced-by-count":7,"title":["Prototype Correction via Contrastive Augmentation for Few-Shot Unconstrained Palmprint Recognition"],"prefix":"10.1109","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8871-1242","authenticated-orcid":false,"given":"Kunlei","family":"Jing","sequence":"first","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"given":"Xinman","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"}]},{"given":"Chen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computing and the School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"given":"Wanyu","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5859-1152","authenticated-orcid":false,"given":"Hebo","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7184-2043","authenticated-orcid":false,"given":"Meng","family":"Pang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer Sciences, Nanchang University, Nanchang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6874-6453","authenticated-orcid":false,"given":"Bihan","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3103941"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.88"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2016.2597291"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01348"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2992219"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2462360"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2911165"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746999"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00760"},{"key":"ref52","first-page":"2845","article-title":"Delta-encoder: An effective sample synthesis method for few-shot object recognition","author":"schwartz","year":"2018","journal-title":"Proc Adv Neural Inf Process Sys"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2903307"},{"key":"ref55","first-page":"2365","article-title":"MetaGAN: An adversarial approach to few-shot learning","author":"zhang","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2705424"},{"key":"ref54","first-page":"975","article-title":"Low-shot learning via covariance-preserving adversarial augmentation networks","author":"gao","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00098"},{"key":"ref16","article-title":"Towards palmprint verification on smartphones","author":"zhang","year":"2020","journal-title":"arXiv 2003 13266"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.12.072"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.28.4.043026"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00888"},{"key":"ref50","article-title":"Free lunch for few-shot learning: Distribution calibration","author":"yang","year":"2021","journal-title":"arXiv 2101 06395"},{"key":"ref46","first-page":"244","article-title":"Learning from small sample sets by combining unsupervised meta-training with CNNs","author":"wang","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3011526"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.328"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2910052"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00781"},{"key":"ref41","first-page":"719","article-title":"TADAM: Task dependent adaptive metric for improved few-shot learning","author":"oreshkin","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093338"},{"key":"ref43","first-page":"1926","article-title":"Adaptive Poincar&#x00E9; point to set distance for few-shot classification","author":"ma","year":"2022","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013379"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.04.016"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2017.014994"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.05.010"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.52"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2945372"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108855"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.153"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00883"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00049"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00755"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4314"},{"key":"ref37","first-page":"4080","article-title":"Prototypical networks for few-shot learning","author":"snell","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","first-page":"3664","article-title":"Rapid adaptation with conditionally shifted neurons","author":"munkhdalai","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref31","first-page":"1","article-title":"Meta-learning with latent embedding optimization","author":"rusu","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2959254"},{"key":"ref30","first-page":"1842","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"finn","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref74","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref33","first-page":"3825","article-title":"LGM-Net: Learning to generate matching networks for few-shot learning","author":"li","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref77","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00011"},{"key":"ref76","first-page":"494","article-title":"Confidence intervals","volume":"1","author":"ci","year":"1987","journal-title":"Lancet"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2015.12.013"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2012.364"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00419"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref71","first-page":"2148","article-title":"Multi-view contrastive graph clustering","author":"pan","year":"2021","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref70","article-title":"Deep robust clustering by contrastive learning","author":"zhong","year":"2020","journal-title":"arXiv 2008 03030"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2945183"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TBIOM.2020.3003406"},{"key":"ref67","first-page":"585","article-title":"Laplacian eigenmaps and spectral techniques for embedding and clustering","author":"belkin","year":"2001","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","first-page":"3630","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3076850"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00436"},{"key":"ref20","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00562"},{"key":"ref63","first-page":"24","article-title":"Deep subspace clustering networks","author":"ji","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3053991"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3079800"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10237-x"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3025666"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2019.00022"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1049\/el.2019.1221"},{"key":"ref29","first-page":"1","article-title":"Optimization as a model for few-shot learning","author":"ravi","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2464090"},{"key":"ref62","first-page":"1925","article-title":"Deep subspace clustering with sparsity prior","author":"peng","year":"2016","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2312322"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/9970396\/10233089.pdf?arnumber=10233089","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T18:13:36Z","timestamp":1695665616000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10233089\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":78,"URL":"https:\/\/doi.org\/10.1109\/tifs.2023.3309458","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}