{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T12:13:33Z","timestamp":1783944813782,"version":"3.55.0"},"reference-count":53,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62371373"],"award-info":[{"award-number":["62371373"]}],"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":["62401418"],"award-info":[{"award-number":["62401418"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.neucom.2026.133964","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T11:09:00Z","timestamp":1778756940000},"page":"133964","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["CSFE-Net: Cycle-consistency scattering feature extraction network for PolSAR image"],"prefix":"10.1016","volume":"694","author":[{"given":"Yue","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biqi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biao","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Licheng","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.133964_bib0005","doi-asserted-by":"crossref","first-page":"2116","DOI":"10.1109\/TGRS.2018.2871504","article-title":"A graph-based semisupervised deep learning model for polsar image classification","volume":"57","author":"Bi","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.neucom.2026.133964_bib0010","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MGRS.2023.3328472","article-title":"Polarimetric roll-invariant features and applications for polarimetric synthetic aperture radar ship detection: a comprehensive summary and investigation","volume":"12","author":"Chen","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Magaz."},{"key":"10.1016\/j.neucom.2026.133964_bib0015","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"627","article-title":"Polsar image classification using polarimetric-feature-driven deep convolutional neural network","volume":"vol. 15","author":"Chen","year":"2018"},{"key":"10.1016\/j.neucom.2026.133964_bib0020","series-title":"Target Scattering Mechanism in Polarimetric Synthetic Aperture Radar","author":"Chen","year":"2018"},{"key":"10.1016\/j.neucom.2026.133964_bib0025","first-page":"1","article-title":"Polsar image classification with multiscale superpixel-based graph convolutional network","volume":"60","author":"Cheng","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0030","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/36.485127","article-title":"A review of target decomposition theorems in radar polarimetry","volume":"34","author":"Cloude","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0035","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MGRS.2023.3237465","article-title":"Explainable, physics-aware, trustworthy artificial intelligence: a paradigm shift for synthetic aperture radar","volume":"11","author":"Datcu","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Magaz."},{"key":"10.1016\/j.neucom.2026.133964_bib0040","article-title":"Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions","volume":"128","author":"Deodoro","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0045","article-title":"In-season crop classification using elements of the kennaugh matrix derived from polarimetric radarsat-2 SAR data","volume":"88","author":"Dey","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0050","first-page":"1","article-title":"A novel causal inference-guided feature enhancement framework for polsar image classification","volume":"62","author":"Dong","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0055","first-page":"1","article-title":"Exploring vision transformers for polarimetric SAR image classification","volume":"60","author":"Dong","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0060","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"1","article-title":"Polsar image classification based on complex-valued convolutional long short-term memory network","volume":"vol. 19","author":"Fang","year":"2022"},{"key":"10.1016\/j.neucom.2026.133964_bib0065","doi-asserted-by":"crossref","first-page":"2583","DOI":"10.1109\/TGRS.2007.897929","article-title":"Fitting a two-component scattering model to polarimetric SAR data from forests","volume":"45","author":"Freeman","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0070","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/JMASS.2024.3381974","article-title":"A complex-valued polsar image segmentation network with lov\u00e1sz-softmax loss optimization","volume":"5","author":"Guo","year":"2024","journal-title":"IEEE J. Miniaturization Air Space Syst."},{"key":"10.1016\/j.neucom.2026.133964_bib0075","article-title":"Built-up area extraction in polsar imagery using real-complex polarimetric features and feature fusion classification network","volume":"134","author":"Guo","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0080","article-title":"Multichannel semi-supervised active learning for polsar image classification","volume":"127","author":"Hua","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0085","doi-asserted-by":"crossref","first-page":"6623","DOI":"10.1109\/TGRS.2020.2978268","article-title":"A patch-to-pixel convolutional neural network for small ship detection with polsar images","volume":"58","author":"Jin","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0090","series-title":"SAR Workshop: CEOS Committee on Earth Observation Satellites","first-page":"335","article-title":"Application of the h\/a\/alpha polarimetric decomposition theorem for unsupervised classification of fully polarimetric SAR data based on the wishart distribution","author":"Lee","year":"2000"},{"key":"10.1016\/j.neucom.2026.133964_bib0095","series-title":"Polarimetric Radar Imaging: from Basics to Applications","author":"Lee","year":"2017"},{"key":"10.1016\/j.neucom.2026.133964_bib0100","first-page":"1","article-title":"Residual in residual scaling networks for polarimetric SAR image despeckling","volume":"61","author":"Lin","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0105","doi-asserted-by":"crossref","first-page":"3292","DOI":"10.1109\/TGRS.2016.2514504","article-title":"Pol-sar image classification based on wishart DBN and local spatial information","volume":"54","author":"Liu","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0110","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1109\/TNNLS.2018.2847309","article-title":"Local restricted convolutional neural network for change detection in polarimetric SAR images","volume":"30","author":"Liu","year":"2018","journal-title":"IEEE Trans. Neur. Net. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.133964_bib0115","series-title":"International Conference on Intelligence Science","first-page":"214","article-title":"Polsf: polsar image datasets on SAN francisco","author":"Liu","year":"2022"},{"key":"10.1016\/j.neucom.2026.133964_bib0120","first-page":"24","article-title":"Joint estimation of plant area index (pai) and wet biomass in wheat and soybean from c-band polarimetric SAR data","volume":"79","author":"Mandal","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0125","doi-asserted-by":"crossref","first-page":"4415","DOI":"10.1109\/TCYB.2020.3026741","article-title":"Online semisupervised active classification for multiview polsar data","volume":"52","author":"Nie","year":"2020","journal-title":"IEEE Trans. Cyber."},{"key":"10.1016\/j.neucom.2026.133964_bib0130","article-title":"Maritime ship detection with concise polarimetric characterization pattern","volume":"131","author":"Quan","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0135","first-page":"1","article-title":"Cnn-improved superpixel-to-pixel fuzzy graph convolution network for polsar image classification","volume":"61","author":"Shi","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0140","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1109\/TCSVT.2024.3456480","article-title":"Content-adaptive multi-region deep network for polarimetric SAR image classification","volume":"35","author":"Shi","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133964_bib0145","first-page":"1","article-title":"Scattering mechanism inspired non-gaussian diffusion model for polarimetric SAR image classification","volume":"63","author":"Shi","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0150","doi-asserted-by":"crossref","first-page":"8371","DOI":"10.1109\/TGRS.2019.2920762","article-title":"Seven-component scattering power decomposition of polsar coherency matrix","volume":"57","author":"Singh","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0155","doi-asserted-by":"crossref","first-page":"5687","DOI":"10.1109\/TGRS.2018.2824322","article-title":"Model-based six-component scattering matrix power decomposition","volume":"56","author":"Singh","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0160","article-title":"Adaptive oil spill detection network for scene-based polsar data using dynamic convolution and boundary constraints","volume":"130","author":"Song","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0165","doi-asserted-by":"crossref","first-page":"3452","DOI":"10.1109\/TGRS.2011.2128325","article-title":"Model-based decomposition of polarimetric SAR covariance matrices constrained for nonnegative eigenvalues","volume":"49","author":"Van Zyl","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0170","article-title":"Multi-resolution soil moisture retrievals by disaggregating smap brightness temperatures with radarsat-2 polarimetric decompositions","volume":"115","author":"Wang","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0175","first-page":"1","article-title":"Translation difference characterization for polsar ship extraction","volume":"64","author":"Wang","year":"2026","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0180","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"1","article-title":"A multichannel fusion convolutional neural network based on scattering mechanism for polsar image classification","volume":"vol. 19","author":"Wang","year":"2021"},{"key":"10.1016\/j.neucom.2026.133964_bib0185","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"1","article-title":"A statistical-spatial feature learning network for polsar image classification","volume":"vol. 19","author":"Wu","year":"2021"},{"key":"10.1016\/j.neucom.2026.133964_bib0190","first-page":"10","article-title":"Water-body types identification in urban areas from radarsat-2 fully polarimetric SAR data","volume":"50","author":"Xie","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"9","key":"10.1016\/j.neucom.2026.133964_bib0195","doi-asserted-by":"crossref","first-page":"9530","DOI":"10.1109\/TCSVT.2025.3558801","article-title":"Vlf-SAR: a novel vision-language framework for few-shot SAR target recognition","volume":"35","author":"Xie","year":"2025","journal-title":"IEEE Trans. Circuits and Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133964_bib0200","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1109\/TGRS.2005.852084","article-title":"Four-component scattering model for polarimetric SAR image decomposition","volume":"43","author":"Yamaguchi","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0205","doi-asserted-by":"crossref","first-page":"8796","DOI":"10.1109\/TGRS.2019.2922978","article-title":"Cnn-based polarimetric decomposition feature selection for polsar image classification","volume":"57","author":"Yang","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0210","article-title":"Ssdfl: spatial scattering decomposition feature learning for polsar image","volume":"128","author":"Yang","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0215","first-page":"1","article-title":"Pdfl: polarimetric decomposition feature learning via deep autoencoder","volume":"60","author":"Yang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0220","article-title":"Unsupervised change detection in polsar images using siamese encoder\u2013decoder framework based on graph-context attention network","volume":"124","author":"Yang","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0225","series-title":"Cyber-Enabled Intelligence","first-page":"67","article-title":"Novel model-based method for identification of scattering mechanisms in polarimetric SAR data","author":"Yin","year":"2019"},{"key":"10.1016\/j.neucom.2026.133964_bib0230","first-page":"1","article-title":"Ts-shes: terrain segmentation in complex-valued polsar images via scattering harmonization and explicit supervision","volume":"60","author":"Zeng","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0235","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"603","article-title":"Multiple-component scattering model for polarimetric SAR image decomposition","volume":"vol. 5","author":"Zhang","year":"2008"},{"key":"10.1016\/j.neucom.2026.133964_bib0240","first-page":"1","article-title":"Learning scattering similarity and texture-based attention with convolutional neural networks for polsar image classification","volume":"61","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0245","doi-asserted-by":"crossref","first-page":"2824","DOI":"10.1109\/TGRS.2018.2877821","article-title":"Ship detection from polsar imagery using the complete polarimetric covariance difference matrix","volume":"57","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0250","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TRS.2025.3631021","article-title":"Polarimeric SAR ship detection based on sub-look the decomposition technology","volume":"4","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Radar Syst."},{"key":"10.1016\/j.neucom.2026.133964_bib0255","article-title":"Forest height estimation combining single-polarization tomographic and polsar data","volume":"124","author":"Zhang","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.neucom.2026.133964_bib0260","doi-asserted-by":"crossref","first-page":"7177","DOI":"10.1109\/TGRS.2017.2743222","article-title":"Complex-valued convolutional neural network and its application in polarimetric SAR image classification","volume":"55","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.133964_bib0265","series-title":"IEEE Geosci. Remote Sens. Lett","first-page":"1935","article-title":"Polarimetric SAR image classification using deep convolutional neural networks","volume":"vol. 13","author":"Zhou","year":"2016"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226013615?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226013615?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T11:50:49Z","timestamp":1783943449000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226013615"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":53,"alternative-id":["S0925231226013615"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133964","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CSFE-Net: Cycle-consistency scattering feature extraction network for PolSAR image","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133964","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"133964"}}