{"id":"https://openalex.org/W4321608682","doi":"https://doi.org/10.1109/tgrs.2023.3244565","title":"Multigranularity Decoupling Network With Pseudolabel Selection for Remote Sensing Image Scene Classification","display_name":"Multigranularity Decoupling Network With Pseudolabel Selection for Remote Sensing Image Scene Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4321608682","doi":"https://doi.org/10.1109/tgrs.2023.3244565"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3244565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3244565","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","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/A5083535665","display_name":"Miao Wang","orcid":"https://orcid.org/0009-0006-8704-4445"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang Miao","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033213528","display_name":"Jie Geng","orcid":"https://orcid.org/0000-0003-4858-823X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Geng","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041289658","display_name":"Wen Jiang","orcid":"https://orcid.org/0000-0001-5429-2748"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Jiang","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083535665"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":11.1136,"has_fulltext":false,"cited_by_count":70,"citation_normalized_percentile":{"value":0.98628546,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8080516457557678},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7535523772239685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6787024140357971},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5926659107208252},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.578129768371582},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.5513397455215454},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.51152503490448},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.47890058159828186},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.473665326833725},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.46615514159202576},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4312078058719635},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4007452428340912},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10119390487670898},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07660442590713501}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8080516457557678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535523772239685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6787024140357971},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5926659107208252},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.578129768371582},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.5513397455215454},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.51152503490448},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47890058159828186},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.473665326833725},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.46615514159202576},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4312078058719635},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4007452428340912},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10119390487670898},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07660442590713501},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","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/tgrs.2023.3244565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3244565","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2645103404","display_name":null,"funder_award_id":"2021YFB3900502","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8527476348","display_name":null,"funder_award_id":"62271396","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W2096945460","https://openalex.org/W2104167780","https://openalex.org/W2151455241","https://openalex.org/W2519867016","https://openalex.org/W2584983011","https://openalex.org/W2605148931","https://openalex.org/W2715220489","https://openalex.org/W2770429219","https://openalex.org/W2793189836","https://openalex.org/W2890732922","https://openalex.org/W2907092121","https://openalex.org/W2945988686","https://openalex.org/W2948329096","https://openalex.org/W2962217138","https://openalex.org/W2983915818","https://openalex.org/W2984353870","https://openalex.org/W2988966271","https://openalex.org/W2994639710","https://openalex.org/W2995197345","https://openalex.org/W2996108195","https://openalex.org/W2996501936","https://openalex.org/W3002497127","https://openalex.org/W3015063979","https://openalex.org/W3022140654","https://openalex.org/W3025900741","https://openalex.org/W3025926153","https://openalex.org/W3034601242","https://openalex.org/W3095707208","https://openalex.org/W3096688134","https://openalex.org/W3100714546","https://openalex.org/W3101627915","https://openalex.org/W3103410140","https://openalex.org/W3105298104","https://openalex.org/W3111381272","https://openalex.org/W3113299742","https://openalex.org/W3119762784","https://openalex.org/W3157699413","https://openalex.org/W3158299003","https://openalex.org/W3167251133","https://openalex.org/W3171921236","https://openalex.org/W3173462278","https://openalex.org/W3177357839","https://openalex.org/W3177541758","https://openalex.org/W3200370304","https://openalex.org/W3202483439","https://openalex.org/W3204140421","https://openalex.org/W3206816884","https://openalex.org/W4206554021","https://openalex.org/W4211114389","https://openalex.org/W4211247672","https://openalex.org/W4213052879","https://openalex.org/W4213253308","https://openalex.org/W4226060438","https://openalex.org/W4226285265","https://openalex.org/W4226291728","https://openalex.org/W4283794091","https://openalex.org/W4285817614","https://openalex.org/W4288020585","https://openalex.org/W4288391342","https://openalex.org/W4290712873","https://openalex.org/W6677082149","https://openalex.org/W6746052068","https://openalex.org/W6762161020","https://openalex.org/W6762913911","https://openalex.org/W6768920361","https://openalex.org/W6770578729","https://openalex.org/W6771630921","https://openalex.org/W6773005947","https://openalex.org/W6780353226","https://openalex.org/W6780957418","https://openalex.org/W6791656692","https://openalex.org/W6802704751","https://openalex.org/W6802739845"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2129933262","https://openalex.org/W3147207884","https://openalex.org/W1836423264"],"abstract_inverted_index":{"The":[0],"existing":[1],"deep":[2,25],"networks":[3,26],"have":[4],"shown":[5],"excellent":[6],"performance":[7,154],"in":[8,29],"remote":[9,56,78],"sensing":[10,57,79],"scene":[11,59],"classification":[12],"(RSSC),":[13],"which":[14,81],"generally":[15],"requires":[16],"a":[17,48,66,94],"large":[18],"amount":[19],"of":[20,89,106],"class-balanced":[21],"training":[22,33],"samples.":[23,108],"However,":[24],"will":[27],"result":[28],"underfitting":[30],"with":[31,156],"imbalanced":[32],"samples":[34],"since":[35],"they":[36],"can":[37],"easily":[38],"bias":[39],"toward":[40],"the":[41,87,90,104,110,121,149],"majority":[42],"classes.":[43],"To":[44,61],"address":[45],"these":[46],"problems,":[47],"multigranularity":[49,67],"decoupling":[50,91],"network":[51],"(MGDNet)":[52],"is":[53,100,117],"proposed":[54,101,150],"for":[55],"image":[58],"classification.":[60],"begin":[62],"with,":[63],"we":[64],"design":[65],"complementary":[68],"feature":[69,113],"representation":[70],"(MGCFR)":[71],"method":[72],"to":[73,85,102,119,124],"extract":[74],"fine-grained":[75],"features":[76,123],"from":[77],"images,":[80],"utilizes":[82],"region-level":[83],"supervision":[84],"guide":[86],"attention":[88],"network.":[92],"Second,":[93],"class-imbalanced":[95],"pseudolabel":[96],"selection":[97],"(CIPS)":[98],"approach":[99],"evaluate":[103],"credibility":[105],"unlabeled":[107],"Finally,":[109],"diversity":[111],"component":[112],"(DCF)":[114],"loss":[115],"function":[116],"developed":[118],"force":[120],"local":[122],"be":[125],"more":[126],"discriminative.":[127],"Our":[128],"model":[129,151],"performs":[130],"satisfactorily":[131],"on":[132],"three":[133],"public":[134],"datasets:":[135],"UC":[136],"Merced":[137],"(UCM),":[138],"NWPU-RESISC45,":[139],"and":[140],"Aerial":[141],"Image":[142],"Dataset":[143],"(AID).":[144],"Experimental":[145],"results":[146],"show":[147],"that":[148],"yields":[152],"superior":[153],"compared":[155],"other":[157],"state-of-the-art":[158],"methods.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":36}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
