{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T04:04:25Z","timestamp":1772856265635,"version":"3.50.1"},"reference-count":46,"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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3022883","type":"journal-article","created":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T20:16:47Z","timestamp":1599682607000},"page":"166335-166346","source":"Crossref","is-referenced-by-count":10,"title":["Maritime Visible Image Classification Based on Double Transfer Method"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7209-8041","authenticated-orcid":false,"given":"Ruiyu","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0588-1594","authenticated-orcid":false,"given":"Jianhua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3610-746X","authenticated-orcid":false,"given":"Xiang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3800-0105","authenticated-orcid":false,"given":"Jing","family":"Wen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5331-7069","authenticated-orcid":false,"given":"Liuzhong","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7552-777X","authenticated-orcid":false,"given":"Junxia","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2292894"},{"key":"ref38","article-title":"Convolution neural networks for ship type recognition","volume":"9844","author":"rainey","year":"2016","journal-title":"Proc 26th Autom Target Recognit"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"ref32","article-title":"A comprehensive survey on transfer learning","author":"zhuang","year":"2019","journal-title":"arXiv 1911 02685"},{"key":"ref31","first-page":"647","article-title":"DeCAF: A deep convolutional activation feature for generic visual recognition","author":"donahue","year":"2014","journal-title":"Proc 31st IEEE Int Conf Mach Learn"},{"key":"ref30","first-page":"3320","article-title":"How transferable are features in deep neural networks","author":"yosinski","year":"2014","journal-title":"Proc Int Conf Advance Neural Inf Process Syst"},{"key":"ref37","article-title":"Image classification with deep learning in the presence of noisy labels: A survey","author":"algan","year":"2019","journal-title":"arXiv 1912 05170"},{"key":"ref36","author":"kim","year":"2020","journal-title":"Semi-Supervised Synthetic-to-Real Domain Adaptation for Fine-Grained Naval Ship Image Classification"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/800057.808710"},{"key":"ref34","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2018.02.017"},{"key":"ref40","article-title":"Challenges in video based object detection in maritime scenario using computer vision","author":"prasad","year":"2016","journal-title":"arXiv 1608 01079"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2015.7301727"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2833258.2833266"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301291"},{"key":"ref14","first-page":"165","article-title":"Marvel: A large-scale image dataset for maritime vessels","author":"gundogdu","year":"2016","journal-title":"Proc Asian Conf Comput Vis (ACCV)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.07.011"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref17","first-page":"1","article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < 0.5mb model size","author":"iandola","year":"2017","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2853620"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/rs11040419"},{"key":"ref28","year":"2020","journal-title":"Vessel Photo Database"},{"key":"ref4","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":"ref27","author":"markit","year":"2018","journal-title":"Statcode 5 Shiptype Coding System&#x2014;A Categorisation of Ships by Type&#x2014;Cargo Carrying Ships"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.23919\/ICIF.2018.8455679"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00121"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00502"},{"key":"ref5","article-title":"Generalizing from a few examples: A survey on few-shot learning","author":"wang","year":"2019","journal-title":"arXiv 1904 05046"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.157"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2634580"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/rs10040511"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2412251"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTIS.2017.8047799"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.183"},{"key":"ref20","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","article-title":"Single image haze removal using dark channel prior","volume":"33","author":"he","year":"2011","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref22","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","author":"tan","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref21","first-page":"460","article-title":"Data augmentation and transfer learning for limited dataset ship classification","volume":"13","author":"milicevic","year":"2018","journal-title":"WSEAS Trans Syst Control"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3008694"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2873791"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00347"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/s18051490"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.5121\/csit.2019.91713"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2877890"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09189876.pdf?arnumber=9189876","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:55:49Z","timestamp":1639770949000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9189876\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3022883","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}