{"id":"https://openalex.org/W4313167432","doi":"https://doi.org/10.1109/igarss46834.2022.9884297","title":"Complex Matrix And Polarimetric Feature Joint Learning For Polarimetric Sar Image Classification","display_name":"Complex Matrix And Polarimetric Feature Joint Learning For Polarimetric Sar Image Classification","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4313167432","doi":"https://doi.org/10.1109/igarss46834.2022.9884297"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884297","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064627220","display_name":"Junfei Shi","orcid":"https://orcid.org/0000-0002-1603-7698"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfei Shi","raw_affiliation_strings":["Xi'an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi'an,China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010131867","display_name":"Haiyan Jin","orcid":"https://orcid.org/0000-0003-3742-4029"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Jin","raw_affiliation_strings":["Xi'an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi'an,China","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210131919"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2714","last_page":"2717"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6918703317642212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6731891632080078},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.6603882312774658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6247338652610779},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6006180644035339},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5308274626731873},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4950041174888611},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4650111794471741},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45767802000045776},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.44905781745910645},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3361886739730835},{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.2288927435874939},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0681154727935791},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06463882327079773}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6918703317642212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6731891632080078},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.6603882312774658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6247338652610779},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6006180644035339},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5308274626731873},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4950041174888611},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4650111794471741},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45767802000045776},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44905781745910645},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3361886739730835},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.2288927435874939},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0681154727935791},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06463882327079773},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884297","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G3094523989","display_name":null,"funder_award_id":"62006186","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2127152713","https://openalex.org/W2546971174","https://openalex.org/W2766130785","https://openalex.org/W2770727026","https://openalex.org/W2962905348","https://openalex.org/W2969632571","https://openalex.org/W2972359265","https://openalex.org/W3006263164","https://openalex.org/W4312593485","https://openalex.org/W6810524219"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2026860918","https://openalex.org/W2035593284","https://openalex.org/W2364594919","https://openalex.org/W2612145225","https://openalex.org/W2225281849","https://openalex.org/W2167092671","https://openalex.org/W2161058488","https://openalex.org/W2324949438","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Nearest-regularized":[0],"subspace":[1],"(NRS)":[2],"algorithm":[3],"is":[4,60,72],"an":[5],"effective":[6],"tool":[7],"to":[8,74,114],"obtain":[9],"both":[10],"accuracy":[11],"and":[12,38,46,54,83,91,106,119,133],"speed":[13],"for":[14,62],"PolSAR":[15,63,131],"image":[16,64],"classification.":[17,65],"However,":[18],"existing":[19],"NRS-based":[20],"methods":[21],"only":[22],"use":[23],"the":[24,29,34,43,88,99,116,121,129,134,137,140],"polarimetric":[25,55],"feature":[26,56],"vector":[27],"as":[28],"input,":[30],"which":[31],"cannot":[32],"learn":[33,42,75],"complex":[35,44,52,80,89],"matrix":[36,45,53,76,81,90],"structure":[37,77],"channel":[39],"information.":[40],"To":[41],"scattering":[47,93],"features":[48,94],"collaboratively,":[49],"a":[50,68],"novel":[51],"joint":[57,96],"learning":[58],"method":[59],"proposed":[61,100,141],"Specifically,":[66],"firstly,":[67],"Riemannian":[69,84],"NRS":[70],"model":[71,101],"utilized":[73,113],"by":[78,98,102],"constructing":[79,103],"dictionary":[82],"distance":[85,108],"metric.":[86],"Then,":[87],"extracted":[92],"are":[95,112,126],"learned":[97],"coupled":[104],"dictionaries":[105],"different":[107],"metrics.":[109],"Besides,":[110],"superpixels":[111],"suppress":[115],"speckle":[117],"noises":[118],"reduce":[120],"computing":[122],"time":[123],"greatly.":[124],"Experiments":[125],"conducted":[127],"on":[128],"real":[130],"data":[132],"results":[135],"demonstrate":[136],"effectiveness":[138],"of":[139],"method.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}