{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T22:39:13Z","timestamp":1780439953695,"version":"3.54.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2021,5,1]],"date-time":"2021-05-01T00:00:00Z","timestamp":1619827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1109\/tgrs.2020.3020427","type":"journal-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T20:34:16Z","timestamp":1600202056000},"page":"3917-3941","source":"Crossref","is-referenced-by-count":68,"title":["\u03a6-Net: Deep Residual Learning for InSAR Parameters Estimation"],"prefix":"10.1109","volume":"59","author":[{"given":"Francescopaolo","family":"Sica","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giorgia","family":"Gobbi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paola","family":"Rizzoli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Bruzzone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898311"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2654543"},{"key":"ref33","first-page":"1","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume":"37","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref31","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref30","article-title":"Going deeper with convolutions","author":"szegedy","year":"2014","journal-title":"arXiv 1409 4842"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.668"},{"key":"ref35","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref34","article-title":"Highway networks","author":"srivastava","year":"2015","journal-title":"arXiv 1505 00387"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2802944"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1515\/cdbme-2018-0072"},{"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":"10.1214\/aoms\/1177704250"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1038\/364138a0","article-title":"The displacement field of the landers earthquake mapped by radar interferometry","volume":"364","author":"massonnet","year":"1993","journal-title":"Nature"},{"key":"ref20","first-page":"679","article-title":"Natural image denoising with convolutional networks","author":"jain","year":"2009","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref21","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2758203"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2017.8128234"},{"key":"ref26","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICSENS.2018.8589665"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.871137"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2010.5651002"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2765761"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.888351"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.scib.2019.03.002"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2012.748992"},{"key":"ref53","year":"2019","journal-title":"Digital Terrain Models of Austria"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2002.802453"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2361919"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1029\/2005RG000183"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1137\/040616024"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2076376"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2352555"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2800087"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/rs10091359"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898886"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839891"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.1994.399711"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1088\/0266-5611\/14\/4\/001"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2012.2202911"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/36.718849"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2003.817212"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2017.08.008"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1029\/1998GL900033"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2002.806997"},{"key":"ref46","first-page":"99","article-title":"Stability of Amazon backscatter at C-band: Spaceborne results from ERS-1\/2 and RADARSAT-1","volume":"450","author":"hawkins","year":"2000","journal-title":"Proc SAR Workshop CEOS Committee Earth Observ Satell Working Group Calibration Validation"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2016.2614103"},{"key":"ref48","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.1994.399352"},{"key":"ref42","author":"cheng","year":"2019","journal-title":"NWPU-Resisc45 Data Set"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2675998"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.900693"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/36.175330"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9410448\/09198099.pdf?arnumber=9198099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T19:28:16Z","timestamp":1643225296000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9198099\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5]]},"references-count":57,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tgrs.2020.3020427","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5]]}}}