{"id":"https://openalex.org/W4416771716","doi":"https://doi.org/10.1109/lgrs.2025.3633179","title":"Lightweight Attention Mechanism With Feature Differences for Efficient Change Detection in Remote Sensing","display_name":"Lightweight Attention Mechanism With Feature Differences for Efficient Change Detection in Remote Sensing","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W4416771716","doi":"https://doi.org/10.1109/lgrs.2025.3633179"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3633179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3633179","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/A5029945691","display_name":"Jangsoo Park","orcid":"https://orcid.org/0009-0005-9312-6781"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jangsoo Park","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0005-9312-6781","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068018422","display_name":"EunSeong Lee","orcid":"https://orcid.org/0000-0001-6996-0809"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"EunSeong Lee","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056683848","display_name":"Jongseok Lee","orcid":"https://orcid.org/0000-0001-8045-0244"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongseok Lee","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-8045-0244","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029538231","display_name":"Seoung\u2010Jun Oh","orcid":"https://orcid.org/0000-0002-7249-3647"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seoung-Jun Oh","raw_affiliation_strings":["Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-7249-3647","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006367195","display_name":"Donggyu Sim","orcid":"https://orcid.org/0000-0002-2794-9932"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Donggyu Sim","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-2794-9932","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161024014"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44198268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","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":0.9926999807357788,"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":0.9926999807357788,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.0026000000070780516,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0007999999797903001,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7803999781608582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6614000201225281},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5835000276565552},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5171999931335449},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5019000172615051},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48910000920295715},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4699000120162964},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.4269999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051999807357788},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7803999781608582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6614000201225281},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5835000276565552},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5205000042915344},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47290000319480896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.42170000076293945},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33719998598098755},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30079999566078186},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.29440000653266907},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3633179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3633179","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/G4446136616","display_name":null,"funder_award_id":"IITP-2025-RS-2022-00156225","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320321374","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1998902551","https://openalex.org/W2145962650","https://openalex.org/W2412588858","https://openalex.org/W2884585870","https://openalex.org/W2891248708","https://openalex.org/W2908320224","https://openalex.org/W3000518130","https://openalex.org/W3027225766","https://openalex.org/W3097082908","https://openalex.org/W3130754787","https://openalex.org/W3154921214","https://openalex.org/W3176330035","https://openalex.org/W4250954493","https://openalex.org/W4312172681","https://openalex.org/W4386299129","https://openalex.org/W4389170058","https://openalex.org/W4408494126","https://openalex.org/W4413822023","https://openalex.org/W4413886996","https://openalex.org/W6884634495"],"related_works":[],"abstract_inverted_index":{"This":[0],"letter":[1],"presents":[2],"a":[3,23,106],"low-complexity":[4],"attention":[5,33,40,53],"module":[6,13,69],"for":[7,127],"fast":[8],"change":[9,37],"detection.":[10],"The":[11],"proposed":[12,96,123],"computes":[14],"the":[15,68,91,95,122],"absolute":[16],"difference":[17],"between":[18],"bi-temporal":[19],"features":[20],"extracted":[21],"by":[22,78,102],"Siamese":[24],"backbone":[25],"network":[26],"and":[27,31,84],"sequentially":[28],"applies":[29],"spatial":[30,43,82],"channel":[32,52],"to":[34,90],"generate":[35],"key":[36],"representations.":[38],"Spatial":[39],"emphasizes":[41],"important":[42],"locations":[44],"using":[45,58],"representative":[46,66],"values":[47,59],"from":[48,60],"channel-wise":[49],"pooling,":[50],"while":[51],"highlights":[54],"discriminative":[55],"feature":[56,79],"responses":[57],"spatial-wise":[61],"pooling.":[62],"By":[63],"leveraging":[64],"low-dimensional":[65],"features,":[67],"significantly":[70],"reduces":[71,98],"computational":[72,135],"cost.":[73],"Additionally,":[74],"its":[75],"dual-attention":[76],"structure\u2014driven":[77],"differences\u2014enhances":[80],"both":[81],"localization":[83],"semantic":[85],"relevance":[86],"of":[87],"changes.":[88],"Compared":[89],"Change-Guided":[92],"Network":[93],"(CGNet),":[94],"method":[97,124],"multiply-accumulate":[99],"operations":[100],"(MACs)":[101],"53.81%":[103],"with":[104,114],"only":[105],"0.15%":[107],"drop":[108],"in":[109],"F1-score,":[110],"demonstrating":[111],"high":[112],"efficiency":[113,136],"minimal":[115],"performance":[116],"degradation.":[117],"These":[118],"results":[119],"suggest":[120],"that":[121],"is":[125,137],"suitable":[126],"large-scale":[128],"or":[129],"real-time":[130],"remote":[131],"sensing":[132],"applications":[133],"where":[134],"essential.":[138]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-14T00:00:00"}
