{"id":"https://openalex.org/W4226022474","doi":"https://doi.org/10.1109/lgrs.2022.3159545","title":"LWCDNet: A Lightweight Fully Convolution Network for Change Detection in Optical Remote Sensing Imagery","display_name":"LWCDNet: A Lightweight Fully Convolution Network for Change Detection in Optical Remote Sensing Imagery","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226022474","doi":"https://doi.org/10.1109/lgrs.2022.3159545"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3159545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3159545","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5032636287","display_name":"Min Han","orcid":"https://orcid.org/0000-0002-2964-4884"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Han","raw_affiliation_strings":["Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Liaoning, China","Professional Technology Innovation Center of Distributed Control for Industrial Equipment of Liaoning Province, Dalian University of Technology, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"Professional Technology Innovation Center of Distributed Control for Industrial Equipment of Liaoning Province, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428065","display_name":"Ran Li","orcid":"https://orcid.org/0000-0002-0393-8833"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]},{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Li","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I4210092944","https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015457299","display_name":"Chengkun Zhang","orcid":"https://orcid.org/0000-0002-3188-6583"},"institutions":[{"id":"https://openalex.org/I116265982","display_name":"Qinghai University","ror":"https://ror.org/05h33bt13","country_code":"CN","type":"education","lineage":["https://openalex.org/I116265982"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengkun Zhang","raw_affiliation_strings":["Department of Computer Technology and Application, Qinghai University, Xining, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Technology and Application, Qinghai University, Xining, China","institution_ids":["https://openalex.org/I116265982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032636287"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":3.3827,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.93127429,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9904000163078308,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8097116947174072},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7649848461151123},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6958333849906921},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6410105228424072},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5835973620414734},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.582821249961853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49154552817344666},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4798942804336548},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.479027658700943},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4646240174770355},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4272496998310089},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.41583794355392456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.379995197057724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32368898391723633},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.17162123322486877},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09943878650665283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07826641201972961},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07448315620422363}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8097116947174072},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7649848461151123},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6958333849906921},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6410105228424072},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5835973620414734},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.582821249961853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49154552817344666},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4798942804336548},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.479027658700943},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4646240174770355},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4272496998310089},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.41583794355392456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.379995197057724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32368898391723633},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.17162123322486877},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09943878650665283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07826641201972961},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07448315620422363},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3159545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3159545","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1431638285","display_name":null,"funder_award_id":"62173063","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2144552105","https://openalex.org/W2795587607","https://openalex.org/W2884585870","https://openalex.org/W2891248708","https://openalex.org/W2951991161","https://openalex.org/W2966542792","https://openalex.org/W2994921959","https://openalex.org/W2996290406","https://openalex.org/W3027225766","https://openalex.org/W3048064159","https://openalex.org/W3130754787","https://openalex.org/W3133438312","https://openalex.org/W3187493547","https://openalex.org/W3197715477","https://openalex.org/W4200000656","https://openalex.org/W6629944422"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W4293226380","https://openalex.org/W3181296946","https://openalex.org/W196800607","https://openalex.org/W2376528221","https://openalex.org/W2359428812","https://openalex.org/W2964954556","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Change":[0],"detection":[1,160],"(CD)":[2],"is":[3,16,96,134],"an":[4],"important":[5],"task":[6],"in":[7,157],"remote":[8,172],"sensing":[9,173],"image":[10],"processing.":[11],"The":[12,166],"main":[13],"research":[14],"goal":[15],"to":[17,77,140],"identify":[18],"whether":[19],"the":[20,26,49,59,69,79,113,120,124,142,154,158,176],"target":[21],"area":[22],"has":[23,31],"changed.":[24],"Recently,":[25],"rise":[27],"of":[28,48,56,71,123,178],"deep":[29],"learning":[30],"provided":[32],"many":[33],"novel":[34],"methods":[35,51],"for":[36,89],"change":[37,90,159],"detection,":[38,91],"and":[39,58,101,108,138],"some":[40],"excellent":[41],"models":[42],"have":[43,52],"been":[44],"proposed.":[45],"However,":[46],"most":[47],"available":[50],"a":[53,84,97,128],"large":[54],"number":[55],"parameters,":[57],"traditional":[60],"loss":[61],"function":[62],"does":[63],"not":[64],"perform":[65],"well":[66],"when":[67],"tackling":[68],"problem":[70],"unbalanced":[72],"sample":[73,155],"number.":[74],"In":[75,126],"order":[76],"solve":[78],"above":[80],"problems,":[81],"we":[82,162],"propose":[83,163],"lightweight":[85],"fully":[86],"convolution":[87,116,121],"network":[88],"namely":[92],"LWCDNet.":[93,179],"Specifically,":[94],"LWCDNet":[95],"typical":[98],"encoder-decoder":[99],"structure,":[100],"it":[102],"realizes":[103],"more":[104,146],"detailed":[105],"information":[106],"transmission":[107],"feature":[109],"extraction":[110],"by":[111,147],"using":[112],"artificial":[114],"padding":[115],"(APC)":[117],"module":[118,132],"as":[119],"unit":[122],"encoder.":[125],"addition,":[127],"convolutional":[129],"block":[130],"attention":[131],"(CBAM)":[133],"added":[135],"between":[136],"encoder":[137],"decoder":[139],"boost":[141],"model’s":[143],"performance":[144],"even":[145],"emphasizing":[148],"critical":[149],"information.":[150],"To":[151],"deal":[152],"with":[153],"imbalance":[156],"task,":[161],"Lov-wce":[164],"loss.":[165],"experimental":[167],"results":[168],"on":[169],"two":[170],"actual":[171],"datasets":[174],"show":[175],"effectiveness":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}