{"id":"https://openalex.org/W4413104882","doi":"https://doi.org/10.1109/jstars.2025.3597776","title":"Multiscale Gaussian Process-Driven Graph Convolutional Neural Network for Polarimetric SAR Image Classification","display_name":"Multiscale Gaussian Process-Driven Graph Convolutional Neural Network for Polarimetric SAR Image Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413104882","doi":"https://doi.org/10.1109/jstars.2025.3597776"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3597776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3597776","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3597776","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075539695","display_name":"Ze-Chen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ze-Chen Li","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015155189","display_name":"Heng-Chao Li","orcid":"https://orcid.org/0000-0002-9735-570X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng-Chao Li","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-9735-570X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jing-Hua Yang","orcid":"https://orcid.org/0000-0001-8207-094X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing-Hua Yang","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-8207-094X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-2058-2373"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Bejing, China"],"raw_orcid":"https://orcid.org/0000-0002-2058-2373","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Bejing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jie Pan","orcid":"https://orcid.org/0009-0001-2548-4684"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Pan","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Bejing, China"],"raw_orcid":"https://orcid.org/0009-0001-2548-4684","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Bejing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5075539695"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25644284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"20929","last_page":"20946"},"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":0.9369999766349792,"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":0.9369999766349792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7110550403594971},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.647621750831604},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.587059736251831},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5769861340522766},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4894198477268219},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4809924364089966},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.47323521971702576},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.4418129324913025},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39710772037506104},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3430268168449402},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.32533568143844604},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14243295788764954},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09637400507926941}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110550403594971},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.647621750831604},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.587059736251831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5769861340522766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4894198477268219},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4809924364089966},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.47323521971702576},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.4418129324913025},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39710772037506104},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3430268168449402},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32533568143844604},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14243295788764954},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09637400507926941},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3597776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3597776","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d28d12c5618f4fdbb85e132664315250","is_oa":true,"landing_page_url":"https://doaj.org/article/d28d12c5618f4fdbb85e132664315250","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 20929-20946 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3597776","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3597776","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1201885732","display_name":null,"funder_award_id":"2682024CX017","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G1445879851","display_name":null,"funder_award_id":"2024M752661","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G1975654480","display_name":null,"funder_award_id":"2024NSFSC1467","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G3900967620","display_name":null,"funder_award_id":"2023NSFSC0030","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G4261569257","display_name":null,"funder_award_id":"12401605","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7509836859","display_name":null,"funder_award_id":"62271418","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"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1986621478","https://openalex.org/W2007689604","https://openalex.org/W2071681365","https://openalex.org/W2076375484","https://openalex.org/W2135957796","https://openalex.org/W2153635508","https://openalex.org/W2171810515","https://openalex.org/W2288201067","https://openalex.org/W2306802236","https://openalex.org/W2729686560","https://openalex.org/W2754361766","https://openalex.org/W2793189836","https://openalex.org/W2800770979","https://openalex.org/W2804824750","https://openalex.org/W2819744022","https://openalex.org/W2897760800","https://openalex.org/W2927127974","https://openalex.org/W2945218594","https://openalex.org/W2963943821","https://openalex.org/W2964229061","https://openalex.org/W2969662039","https://openalex.org/W2979476850","https://openalex.org/W2991494819","https://openalex.org/W3002179192","https://openalex.org/W3036475713","https://openalex.org/W3037944168","https://openalex.org/W3043426275","https://openalex.org/W3047774572","https://openalex.org/W3107540033","https://openalex.org/W3124574862","https://openalex.org/W3132371805","https://openalex.org/W3152893301","https://openalex.org/W3159220375","https://openalex.org/W3160731713","https://openalex.org/W3165071532","https://openalex.org/W3177168257","https://openalex.org/W3216960684","https://openalex.org/W4211049957","https://openalex.org/W4292543309","https://openalex.org/W4312204377","https://openalex.org/W4312723186","https://openalex.org/W4381244723","https://openalex.org/W4384283977","https://openalex.org/W4387885787","https://openalex.org/W4394805149","https://openalex.org/W4399039901","https://openalex.org/W4399728165","https://openalex.org/W4400646820","https://openalex.org/W4402350668","https://openalex.org/W4404479756","https://openalex.org/W4410291760"],"related_works":["https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W2963346891","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661","https://openalex.org/W1964286703","https://openalex.org/W2169866437"],"abstract_inverted_index":{"By":[0],"focusing":[1],"on":[2,185],"the":[3,39,60,85,90,102,119,125,130,143,163,173,192],"structure":[4],"exploration":[5],"and":[6,22,57,87,123,133,172],"information":[7,137],"propagation":[8],"from":[9],"non-Euclidean":[10],"data":[11],"space,":[12],"graph":[13],"convolutional":[14],"neural":[15],"network":[16],"(GCN),":[17],"which":[18,99],"can":[19,100,179,195],"extract":[20],"abundant":[21],"discriminative":[23],"features,":[24],"has":[25],"been":[26],"a":[27,69,151],"valuable":[28],"topic":[29],"in":[30,113],"polarimetric":[31,61,70,153],"synthetic":[32],"aperture":[33],"radar":[34],"(PolSAR)":[35],"image":[36,80],"field.":[37],"However,":[38],"existing":[40],"GCN-based":[41,203],"PolSAR":[42,79,187],"classification":[43,204],"methods":[44],"have":[45],"high":[46],"computational":[47],"cost,":[48],"may":[49],"easily":[50],"be":[51,180],"prone":[52],"to":[53,141],"over-smoothing":[54,86],"or":[55,148],"over-fitting,":[56],"inadequately":[58],"learn":[59],"property.":[62],"To":[63],"address":[64],"these":[65],"issues,":[66],"we":[67,117],"propose":[68],"rotation-based":[71,154],"multi-scale":[72,120,126],"Gaussian":[73,91],"process-driven":[74],"GCN":[75,97],"(MGPGCN)":[76],"for":[77,83,128],"semi-supervised":[78],"classification.":[81],"Firstly,":[82],"addressing":[84],"over-fitting":[88],"problems,":[89],"process":[92],"(GP)":[93],"is":[94,158,169],"introduced":[95],"into":[96],"framework,":[98],"fit":[101],"underlying":[103],"feature":[104,155],"distribution":[105],"rather":[106],"than":[107],"calculating":[108],"specific":[109],"values":[110],"of":[111,138,165,176],"weights":[112],"conventional":[114],"GCN.":[115,139],"Secondly,":[116],"extend":[118],"layer":[121],"architecture":[122],"design":[124],"kernel":[127,178],"improving":[129],"representation":[131,174],"capability":[132,175],"fully":[134],"leveraging":[135],"neighborhood":[136],"Thirdly,":[140],"mitigate":[142],"effect":[144],"caused":[145],"by":[146],"noise":[147],"imaging":[149],"angle,":[150],"superpixel-level":[152],"enhancement":[156],"strategy":[157],"designed.":[159],"With":[160],"this":[161],"strategy,":[162],"characteristic":[164],"each":[166],"terrain":[167],"type":[168],"more":[170],"salient,":[171],"GP":[177],"further":[181],"improved.":[182],"Comprehensive":[183],"experiments":[184],"three":[186],"datasets":[188],"firmly":[189],"demonstrate":[190],"that":[191],"proposed":[193],"MGPGCN":[194],"achieve":[196],"better":[197],"performance":[198],"compared":[199],"with":[200],"some":[201],"widely-used":[202],"methods.":[205]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
