{"id":"https://openalex.org/W4409580845","doi":"https://doi.org/10.1109/lgrs.2025.3562480","title":"CDxLSTM: Boosting Remote Sensing Change Detection With Extended Long Short-Term Memory","display_name":"CDxLSTM: Boosting Remote Sensing Change Detection With Extended Long Short-Term Memory","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409580845","doi":"https://doi.org/10.1109/lgrs.2025.3562480"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3562480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3562480","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/A5101514142","display_name":"Zhenkai Wu","orcid":"https://orcid.org/0009-0000-0613-0584"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenkai Wu","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-0613-0584","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652936","display_name":"Xiaowen Ma","orcid":"https://orcid.org/0000-0001-5031-2641"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowen Ma","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5031-2641","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109737165","display_name":"Rongrong Lian","orcid":"https://orcid.org/0009-0005-3262-6651"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongrong Lian","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-3262-6651","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kai Zheng","orcid":"https://orcid.org/0009-0005-1839-476X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zheng","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-1839-476X","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032869178","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-4424-079X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4424-079X","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.5496,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.97248054,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"22","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":0.9731000065803528,"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":0.9731000065803528,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7238399386405945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6088838577270508},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5452736616134644},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5096383094787598},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4645402729511261},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4218134582042694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29196444153785706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10311871767044067},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08058586716651917}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7238399386405945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6088838577270508},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5452736616134644},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5096383094787598},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4645402729511261},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4218134582042694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29196444153785706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10311871767044067},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08058586716651917},{"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/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"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":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3562480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3562480","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":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G3695305740","display_name":null,"funder_award_id":"2022S125","funder_id":"https://openalex.org/F4320327798","funder_display_name":"Science and Technology Project of Longyan City"},{"id":"https://openalex.org/G4342912974","display_name":null,"funder_award_id":"2023Z130","funder_id":"https://openalex.org/F4320336552","funder_display_name":"Science and Technology Innovation 2025 Major Project of Ningbo"}],"funders":[{"id":"https://openalex.org/F4320327798","display_name":"Science and Technology Project of Longyan City","ror":null},{"id":"https://openalex.org/F4320336552","display_name":"Science and Technology Innovation 2025 Major Project of Ningbo","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2015780366","https://openalex.org/W2891248708","https://openalex.org/W2896092083","https://openalex.org/W2908320224","https://openalex.org/W2962914239","https://openalex.org/W2967626412","https://openalex.org/W3011156941","https://openalex.org/W3015038817","https://openalex.org/W3027225766","https://openalex.org/W3036453075","https://openalex.org/W3099503507","https://openalex.org/W3120467244","https://openalex.org/W3130754787","https://openalex.org/W3180045188","https://openalex.org/W3216244838","https://openalex.org/W4285298122","https://openalex.org/W4312549298","https://openalex.org/W4312724722","https://openalex.org/W4360930410","https://openalex.org/W4382240924","https://openalex.org/W4382317739","https://openalex.org/W4385245566","https://openalex.org/W4385863649","https://openalex.org/W4390874124","https://openalex.org/W4394007483","https://openalex.org/W4400448280","https://openalex.org/W4405811875","https://openalex.org/W4406259050","https://openalex.org/W6859298233","https://openalex.org/W6861342692","https://openalex.org/W6866443539","https://openalex.org/W6869044990","https://openalex.org/W6870011642","https://openalex.org/W6875842941","https://openalex.org/W6876739785"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W2147697413","https://openalex.org/W2154063878","https://openalex.org/W4231274751","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W4401807425"],"abstract_inverted_index":{"In":[0,45],"complex":[1],"scenes":[2],"and":[3,26,36,41,73,94,140],"varied":[4],"conditions,":[5],"effectively":[6],"integrating":[7,63],"spatial-temporal":[8],"context":[9,71],"is":[10,56,143],"crucial":[11],"for":[12,90,100],"accurately":[13],"identifying":[14],"changes.":[15],"However,":[16],"current":[17],"RS-CD":[18],"methods":[19],"lack":[20,29],"a":[21,52,57,79,85,95,107,135],"balanced":[22],"consideration":[23],"of":[24,66],"performance":[25,129],"efficiency.":[27],"CNNs":[28],"global":[30,70,115],"context,":[31],"Transformers":[32],"are":[33],"computationally":[34],"expensive,":[35],"Mambas":[37],"face":[38],"CUDA":[39],"dependence":[40],"local":[42],"correlation":[43],"loss.":[44],"this":[46],"paper,":[47],"we":[48,77,105],"propose":[49,106],"CDXLSTM,":[50],"with":[51,118],"core":[53],"component":[54],"that":[55,125],"powerful":[58],"XLSTM-based":[59],"feature":[60],"enhancement":[61],"layer,":[62,83],"the":[64],"advantages":[65],"linear":[67],"computational":[68],"complexity,":[69],"perception,":[72],"strong":[74],"interpret-ability.":[75],"Specifically,":[76],"introduce":[78],"scale-specific":[80],"Feature":[81],"Enhancer":[82],"incorporating":[84],"Cross-Temporal":[86,96],"Global":[87],"Perceptron":[88],"customized":[89,99],"semantic-accurate":[91],"deep":[92],"features,":[93],"Spatial":[97],"Refiner":[98],"detail-rich":[101],"shallow":[102],"features.":[103],"Additionally,":[104],"Cross-Scale":[108],"Interactive":[109],"Fusion":[110],"module":[111],"to":[112],"progressively":[113],"interact":[114],"change":[116],"representations":[117],"spatial":[119],"responses.":[120],"Extensive":[121],"experimental":[122],"results":[123],"demonstrate":[124],"CDXLSTM":[126],"achieves":[127],"state-of-the-art":[128],"across":[130],"three":[131],"benchmark":[132],"datasets,":[133],"offering":[134],"compelling":[136],"balance":[137],"between":[138],"efficiency":[139],"accuracy.":[141],"Code":[142],"available":[144],"at":[145],"https://github.com/xwmaxwma/rschange.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}
