{"id":"https://openalex.org/W3200126366","doi":"https://doi.org/10.3390/rs13183579","title":"Decision-Level Fusion with a Pluginable Importance Factor Generator for Remote Sensing Image Scene Classification","display_name":"Decision-Level Fusion with a Pluginable Importance Factor Generator for Remote Sensing Image Scene Classification","publication_year":2021,"publication_date":"2021-09-08","ids":{"openalex":"https://openalex.org/W3200126366","doi":"https://doi.org/10.3390/rs13183579","mag":"3200126366"},"language":"en","primary_location":{"id":"doi:10.3390/rs13183579","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13183579","pdf_url":"https://www.mdpi.com/2072-4292/13/18/3579/pdf?version=1631104048","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/13/18/3579/pdf?version=1631104048","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081646661","display_name":"Junge Shen","orcid":"https://orcid.org/0000-0002-6563-9206"},"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":"Junge Shen","raw_affiliation_strings":["Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China"],"affiliations":[{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610540","display_name":"Chi Zhang","orcid":"https://orcid.org/0000-0002-4899-2745"},"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":"Chi Zhang","raw_affiliation_strings":["Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China"],"affiliations":[{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102810208","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0003-3708-3543"},"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"]},{"id":"https://openalex.org/I68581759","display_name":"China Academy of Launch Vehicle Technology","ror":"https://ror.org/012z62f48","country_code":"CN","type":"facility","lineage":["https://openalex.org/I68581759"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["China Academy of Launch Vehicle Technology, Beijing 100076, China","Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China"],"affiliations":[{"raw_affiliation_string":"China Academy of Launch Vehicle Technology, Beijing 100076, China","institution_ids":["https://openalex.org/I68581759"]},{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101848673","display_name":"Ruxin Wang","orcid":"https://orcid.org/0000-0002-2730-9409"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruxin Wang","raw_affiliation_strings":["Engineering Research Center of Cyberspace, School of Software, Yunnan University, Kunming 650504, China"],"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Cyberspace, School of Software, Yunnan University, Kunming 650504, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101848673"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.8726,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77267509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"13","issue":"18","first_page":"3579","last_page":"3579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9912999868392944,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7809411287307739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6002620458602905},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5529619455337524},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5269858837127686},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5199505090713501},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5084902048110962},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49971628189086914},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4932190775871277},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4799221456050873},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4500274956226349},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.44627249240875244},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44495829939842224},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.43207627534866333},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41566604375839233},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4023168981075287},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38216960430145264},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3747696876525879},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34545689821243286},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07239341735839844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7809411287307739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6002620458602905},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5529619455337524},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5269858837127686},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5199505090713501},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5084902048110962},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49971628189086914},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4932190775871277},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4799221456050873},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4500274956226349},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.44627249240875244},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44495829939842224},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43207627534866333},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41566604375839233},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4023168981075287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38216960430145264},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3747696876525879},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34545689821243286},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07239341735839844},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13183579","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13183579","pdf_url":"https://www.mdpi.com/2072-4292/13/18/3579/pdf?version=1631104048","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f5d5d719ae1d4b5e9aac4a8985268e14","is_oa":true,"landing_page_url":"https://doaj.org/article/f5d5d719ae1d4b5e9aac4a8985268e14","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 13, Iss 18, p 3579 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/18/3579/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13183579","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 13; Issue 18; Pages: 3579","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13183579","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13183579","pdf_url":"https://www.mdpi.com/2072-4292/13/18/3579/pdf?version=1631104048","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7699999809265137,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G5433545843","display_name":null,"funder_award_id":"51909206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8621529372","display_name":null,"funder_award_id":"61603233","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320314997","display_name":"Strong","ror":"https://ror.org/041vyzr56"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3200126366.pdf","grobid_xml":"https://content.openalex.org/works/W3200126366.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1958291604","https://openalex.org/W1980038761","https://openalex.org/W2005368619","https://openalex.org/W2122282653","https://openalex.org/W2129826572","https://openalex.org/W2145072179","https://openalex.org/W2194775991","https://openalex.org/W2203240275","https://openalex.org/W2248805833","https://openalex.org/W2253590344","https://openalex.org/W2291068538","https://openalex.org/W2347115704","https://openalex.org/W2514386985","https://openalex.org/W2515866431","https://openalex.org/W2546523301","https://openalex.org/W2592962403","https://openalex.org/W2610166850","https://openalex.org/W2621526417","https://openalex.org/W2783165089","https://openalex.org/W2799466885","https://openalex.org/W2829067510","https://openalex.org/W2890732922","https://openalex.org/W2902666195","https://openalex.org/W2912089046","https://openalex.org/W2917187459","https://openalex.org/W2919352650","https://openalex.org/W2920232463","https://openalex.org/W2923696186","https://openalex.org/W2946057160","https://openalex.org/W2948329096","https://openalex.org/W2951023065","https://openalex.org/W2954156245","https://openalex.org/W2970844248","https://openalex.org/W2972420818","https://openalex.org/W2974035141","https://openalex.org/W2974770574","https://openalex.org/W2976087772","https://openalex.org/W2986888765","https://openalex.org/W2998002262","https://openalex.org/W2999338704","https://openalex.org/W3004372116","https://openalex.org/W3027629341","https://openalex.org/W3030221510","https://openalex.org/W3035984349","https://openalex.org/W3080321686","https://openalex.org/W3095319281","https://openalex.org/W3103856189","https://openalex.org/W3105577662","https://openalex.org/W3113299742","https://openalex.org/W3121292405","https://openalex.org/W3127899546","https://openalex.org/W3154634026","https://openalex.org/W3162006265","https://openalex.org/W6683411478","https://openalex.org/W6787429747"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,12,75],"image":[2,13,52,76],"scene":[3],"classification":[4,125,210],"acts":[5],"as":[6],"an":[7,104],"important":[8],"task":[9],"in":[10,32,50,61,158,215],"remote":[11,74],"applications,":[14],"which":[15,99],"benefits":[16],"from":[17],"the":[18,35,42,51,55,62,70,73,79,93,96,129,156,165,169,182,185,190,194,216,225,230,234,238,243,246],"pleasing":[19],"performance":[20,94],"brought":[21],"by":[22,174],"deep":[23,30,63,97],"convolution":[24],"neural":[25],"networks":[26],"(CNNs).":[27],"When":[28],"applying":[29],"models":[31],"this":[33],"task,":[34],"challenges":[36],"are,":[37],"on":[38,69,128,181,220],"one":[39],"hand,":[40,72],"that":[41,110,122,142,207],"targets":[43,57],"with":[44,113,162],"highly":[45],"different":[46,133,159,197],"scales":[47],"may":[48],"exist":[49],"simultaneously":[53],"and":[54,68,85,177,184,237],"small":[56],"could":[58,91],"be":[59],"lost":[60],"feature":[64,130],"maps":[65,131],"of":[66,81,95,132,196,245],"CNNs;":[67],"other":[71,250],"data":[77],"exhibits":[78],"properties":[80],"high":[82,86],"inter-class":[83],"similarity":[84],"intra-class":[87],"variance.":[88],"Both":[89],"factors":[90,152],"limit":[92],"models,":[98],"motivates":[100],"us":[101],"to":[102,164,212],"develop":[103,136],"adaptive":[105],"decision-level":[106,203,217],"information":[107],"fusion":[108,204],"framework":[109],"can":[111],"incorporate":[112],"any":[114],"CNN":[115,120],"backbones.":[116],"Specifically,":[117],"given":[118],"a":[119,137,146,175,201],"backbone":[121],"predicts":[123],"multiple":[124],"scores":[126,157,183,195],"based":[127,180],"layers,":[134,198],"we":[135,199],"pluginable":[138],"importance":[139],"factor":[140,147],"generator":[141],"aims":[143],"at":[144],"predicting":[145],"for":[148],"each":[149,209],"score.":[150],"The":[151],"measure":[153],"how":[154],"confident":[155],"layers":[160],"are":[161],"respect":[163],"final":[166,170],"output.":[167],"Formally,":[168],"score":[171,211],"is":[172],"obtained":[173],"class-wise":[176],"weighted":[178],"summation":[179],"corresponding":[186],"factors.":[187],"To":[188],"reduce":[189],"co-adaptation":[191],"effect":[192],"among":[193],"propose":[200],"stochastic":[202],"training":[205],"strategy":[206],"enables":[208],"randomly":[213],"participate":[214],"fusion.":[218],"Experiments":[219],"four":[221],"popular":[222],"datasets":[223],"including":[224],"UC":[226],"Merced":[227],"Land-Use":[228],"dataset,":[229,233,236],"RSSCN":[231],"7":[232],"AID":[235],"NWPU-RESISC":[239],"45":[240],"dataset":[241],"demonstrate":[242],"superiority":[244],"proposed":[247],"method":[248],"over":[249],"state-of-the-art":[251],"methods.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-09-27T00:00:00"}
