{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T07:10:43Z","timestamp":1778569843988,"version":"3.51.4"},"reference-count":54,"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-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42075140"],"award-info":[{"award-number":["42075140"]}],"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":["41575046"],"award-info":[{"award-number":["41575046"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Commonwealth Techniques and Application Research of Zhejiang Province","award":["LGF20D050004"],"award-info":[{"award-number":["LGF20D050004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/jstars.2021.3050767","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T19:32:44Z","timestamp":1610566364000},"page":"2070-2086","source":"Crossref","is-referenced-by-count":103,"title":["Tropical Cyclone Intensity Classification and Estimation Using Infrared Satellite Images With Deep Learning"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2170-3878","authenticated-orcid":false,"given":"Chang-Jiang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Jie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0103-5830","authenticated-orcid":false,"given":"Lei-Ming","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Qin","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2427035"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04410-7"},{"key":"ref33","first-page":"4278","article-title":"Inception-v4, inception-ResNet and the impact of residual connections on learning","author":"szegedy","year":"0","journal-title":"31st AAAI Conf Artif Intell"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref30","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/Multi-Temp.2019.8866970"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-18-0136.1"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2766358"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2938204"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-15-0100.1"},{"key":"ref29","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":"ref2","doi-asserted-by":"publisher","DOI":"10.1029\/2004GL022045"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0477(2000)081<1241:SAOTCU>2.3.CO;2"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/atmos7030040"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.2151\/sola.2019-034"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-13-00006.1"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3874-6"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s42452-019-1134-8"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2894654"},{"key":"ref25","first-page":"581","article-title":"Eyed tropical cyclone intensity objective estimation model based on infrared satellite image and relevance vector machine","volume":"22","author":"dai","year":"2018","journal-title":"J Remote Sens"},{"key":"ref50","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume":"28","author":"shi","year":"2015","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1029\/2018GL079997"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-16-0220.1"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1002\/joc.6348"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1175\/MWR-D-18-0309.1"},{"key":"ref10","first-page":"268","article-title":"Tropical cyclone intensity analysis using enhanced infrared satellite data","author":"dvorak","year":"1977","journal-title":"Proc 11th Tech Conf Hurricanes Trop Meteorol"},{"key":"ref11","article-title":"Satellite applications at the joint typhoon warning center. Rapporteur Report, Topic 0.1 e","volume":"1136","author":"engel","year":"2002","journal-title":"Proc 5th WMO Int Workshop Tropical Cyclones"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"2261","DOI":"10.1175\/MWR-D-18-0391.1","article-title":"Using deep learning to estimate tropical cyclone intensity from satellite passive microwave imagery","volume":"147","author":"wimmers","year":"2019","journal-title":"Monthly Weather Rev"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1175\/WAF975.1","article-title":"The advanced Dvorak technique: Continued development of an objective scheme to estimate tropical cyclone intensity using geostationary infrared satellite imagery","volume":"22","author":"olander","year":"2007","journal-title":"Wea Forecasting"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1175\/WAF985.1"},{"key":"ref14","first-page":"52","article-title":"Objective estimation of tropical cyclone intensity based on satellite data","volume":"25","author":"lu","year":"2014","journal-title":"J Appl Meteorol"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-19-0007.1"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2008.2000819"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-10-05062.1"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1175\/WAF-D-13-00133.1","article-title":"Satellite-derived tropical cyclone intensity in the north Pacific ocean using the deviation-angle variance technique","volume":"29","author":"ritchie","year":"2014","journal-title":"Weather Forecasting"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2015.1009647"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1175\/JTECH-D-15-0128.1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2011.2153862"},{"key":"ref6","first-page":"1612","article-title":"Synergistic use of satellite active and passive microwave observations to estimate typhoon intensity","author":"yang","year":"0","journal-title":"Proc Photon Electromagn Res Symp -Spring"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1175\/JAMC-D-18-0094.1"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0493(1975)103<0420:TCIAAF>2.0.CO;2"},{"key":"ref7","first-page":"19","article-title":"A technique for the analysis and forecasting of tropicalcyclone intensities from satellite pictures","volume":"45","author":"dvorak","year":"1973","journal-title":"NOAA Technical Memorandum NESS"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref9","article-title":"Tropical cyclone intensity analysis using satellite data","volume":"11","author":"dvorak","year":"1984","journal-title":"NOAA Technical Report NESDIS"},{"key":"ref46","article-title":"ADADELTA: An adaptive learning rate method","author":"zeiler","year":"2012"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref48","article-title":"An update on the CIMSS SATellite CONsensus (SATCON) tropical cyclone intensity algorithm","author":"velden","year":"2019","journal-title":"Proc Joint Satell Conf"},{"key":"ref47","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-11-00156.1"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8545593"},{"key":"ref44","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref43","first-page":"3","article-title":"CBAM: Convolutional block attention module","author":"woo","year":"0","journal-title":"Proc Eur Conf Comput Vis"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4609443\/9314330\/09320562.pdf?arnumber=9320562","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T11:19:17Z","timestamp":1643282357000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9320562\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/jstars.2021.3050767","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"value":"1939-1404","type":"print"},{"value":"2151-1535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}