{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T06:50:52Z","timestamp":1774162252293,"version":"3.50.1"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100007406","name":"Leonardo Grants for Researchers and Cultural Creators awarded by the Fundaci\u00f3n BBVA","doi-asserted-by":"publisher","award":["2021\/00203\/00"],"award-info":[{"award-number":["2021\/00203\/00"]}],"id":[{"id":"10.13039\/100007406","id-type":"DOI","asserted-by":"publisher"}]},{"name":"eNMoLabs Research Project"},{"DOI":"10.13039\/501100005367","name":"CiberGID UNED Innovation Group through the CiberScratch Project","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005367","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005367","name":"I4Labs UNED Research Group","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005367","id-type":"DOI","asserted-by":"publisher"}]},{"name":"E-Madrid-CM Network of Excellence","award":["S2018\/TCS-4307"],"award-info":[{"award-number":["S2018\/TCS-4307"]}]},{"name":"SNOLA, officially recognized Thematic Network of Excellence by the Spanish Ministry of Science, Innovation and Universities","award":["RED2018-102725-T"],"award-info":[{"award-number":["RED2018-102725-T"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3107626","type":"journal-article","created":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T20:13:43Z","timestamp":1629836023000},"page":"118419-118434","source":"Crossref","is-referenced-by-count":10,"title":["SiCoDeF\u00b2 Net: Siamese Convolution Deconvolution Feature Fusion Network for One-Shot Classification"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6580-3977","authenticated-orcid":false,"given":"Swalpa Kumar","family":"Roy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Purbayan","family":"Kar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1030-3729","authenticated-orcid":false,"given":"Mercedes E.","family":"Paoletti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6701-961X","authenticated-orcid":false,"given":"Juan M.","family":"Haut","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4089-9538","authenticated-orcid":false,"given":"Rafael","family":"Pastor-Vargas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5181-0199","authenticated-orcid":false,"given":"Antonio","family":"Robles-Gomez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref73","first-page":"1","article-title":"Labeled faces in the wild: A database forstudying face recognition in unconstrained environments","author":"huang","year":"2008","journal-title":"Proc Workshop Faces Real-Life Images Detection Alignment Recognit"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-27101-9_26"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.92"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.2000.840647"},{"key":"ref76","article-title":"LiSHT: Non-parametric linearly scaled hyperbolic tangent activation function for neural networks","author":"roy","year":"2019","journal-title":"arXiv 1901 05894"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459197"},{"key":"ref75","article-title":"Mish: A self regularized non-monotonic activation function","author":"misra","year":"2019","journal-title":"arXiv 1908 08681"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.202"},{"key":"ref78","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":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298907"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2833032"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.220"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.244"},{"key":"ref37","article-title":"Learning face representation from scratch","author":"yi","year":"2014","journal-title":"arXiv 1411 7923"},{"key":"ref36","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.41"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref60","article-title":"Fast inverse square root","author":"lomont","year":"2003"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.170"},{"key":"ref61","first-page":"807","article-title":"Rectified linear units improve restricted Boltzmann machines","author":"nair","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn (ICML)"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477593"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2015.7358802"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.20"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2035882"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2012.38"},{"key":"ref66","first-page":"521","article-title":"Distance metric learning with application to clustering with side-information","author":"xing","year":"2003","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2408431"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00020"},{"key":"ref68","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ACV.1994.341300"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI.2018.00067"},{"key":"ref1","first-page":"69","article-title":"RBPCA MaxLike: A novel statistic classifier for face recognition based on block-based PCA and covariance matrix regularization","author":"salvadeo","year":"2010","journal-title":"Proc 17th Int Conf Syst Signals Image Process"},{"key":"ref20","first-page":"2545","article-title":"The do&#x2019;s and don&#x2019;ts for CNN-based face verification","author":"bansal","year":"2017","journal-title":"Proc IEEE Int Conf Comput Vis Workshops"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.244"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.05.025"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2005.147"},{"key":"ref23","first-page":"1e","article-title":"Computer vision using local binary patterns","author":"pietik\u00e4inen","year":"2011","journal-title":"Computer Vision Using Local Binary Patterns"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.389"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.884956"},{"key":"ref50","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.758"},{"key":"ref59","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"arXiv 1502 03167"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2019.11.032"},{"key":"ref57","article-title":"SigNet: Convolutional Siamese network for writer independent offline signature verification","author":"dey","year":"2017","journal-title":"arXiv 1707 02131"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref55","first-page":"1","article-title":"Network deconvolution","author":"ye","year":"2020","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00951"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00095"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2003.1211486"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2188809"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273523"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/5.381842"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2017.8272731"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/34.598228"},{"key":"ref15","first-page":"1988","article-title":"Deep learning face representation by joint identification-verification","author":"sun","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2603535"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477557"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.03.013"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3745\/JIPS.2009.5.2.041"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSN.2011.6014865"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/72.554195"},{"key":"ref6","first-page":"20","article-title":"Face recognition in uncontrolled environments, experiments in an airport","author":"conde","year":"2011","journal-title":"Proc Int Conf E-Bus Telecommun"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.68"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/954339.954342"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2016.2593919"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00353"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0620-5"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.01.092"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/7068349"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.420"},{"key":"ref47","article-title":"DSD: Dense-sparse-dense training for deep neural networks","author":"han","year":"2016","journal-title":"arXiv 1607 04381"},{"key":"ref42","first-page":"1","article-title":"Siamese neural networks for one-shot image recognition","volume":"2","author":"koch","year":"2015","journal-title":"Proc ICML Deep Learn Workshop"},{"key":"ref41","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":"ref44","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":"ref43","first-page":"1601","article-title":"Do convnets learn correspondence?","author":"long","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09521872.pdf?arnumber=9521872","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:57:38Z","timestamp":1639771058000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9521872\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":78,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3107626","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}