{"id":"https://openalex.org/W4400977327","doi":"https://doi.org/10.1109/tgrs.2024.3433373","title":"Multiscale Alignment and Progressive Feature Fusion Network for High Resolution Remote Sensing Images Change Detection","display_name":"Multiscale Alignment and Progressive Feature Fusion Network for High Resolution Remote Sensing Images Change Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400977327","doi":"https://doi.org/10.1109/tgrs.2024.3433373"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3433373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3433373","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/A5100706940","display_name":"Feng Zhao","orcid":"https://orcid.org/0000-0002-0323-9573"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhao","raw_affiliation_strings":["School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0323-9573","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012884039","display_name":"Zhenglin Zhu","orcid":"https://orcid.org/0009-0002-5166-4408"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenglin Zhu","raw_affiliation_strings":["School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0002-5166-4408","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005672975","display_name":"Hanqiang Liu","orcid":"https://orcid.org/0000-0001-8774-8625"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqiang Liu","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-8774-8625","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi’an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038759055","display_name":"Junjie Zhang","orcid":"https://orcid.org/0000-0002-0895-3127"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Zhang","raw_affiliation_strings":["School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0895-3127","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2744,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79995865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"62","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":0.9969000220298767,"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":0.9969000220298767,"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":0.9921000003814697,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9692000150680542,"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/change-detection","display_name":"Change detection","score":0.7376401424407959},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6600741744041443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6507828831672668},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5556384325027466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.502312421798706},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.4914511442184448},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.47581416368484497},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.46824324131011963},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.46211129426956177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4600823223590851},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44875937700271606},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.44723063707351685},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.44696566462516785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38062340021133423},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2221386730670929},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16050580143928528}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.7376401424407959},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6600741744041443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6507828831672668},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5556384325027466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.502312421798706},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.4914511442184448},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.47581416368484497},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.46824324131011963},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.46211129426956177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4600823223590851},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44875937700271606},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.44723063707351685},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.44696566462516785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38062340021133423},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2221386730670929},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16050580143928528},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3433373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3433373","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":[],"awards":[{"id":"https://openalex.org/G3596670186","display_name":null,"funder_award_id":"62106196","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G515165631","display_name":null,"funder_award_id":"62071379","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8249765525","display_name":"\u5706\u5f62\u76f4\u65b9\u56fe\u9608\u503c\u5206\u5272\u6cd5\u7814\u7a76","funder_award_id":"62071378","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":52,"referenced_works":["https://openalex.org/W10703220","https://openalex.org/W1901129140","https://openalex.org/W2009175701","https://openalex.org/W2073134030","https://openalex.org/W2088557643","https://openalex.org/W2140023211","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2592939477","https://openalex.org/W2601564443","https://openalex.org/W2884436604","https://openalex.org/W2891248708","https://openalex.org/W2908320224","https://openalex.org/W2921458013","https://openalex.org/W2951991161","https://openalex.org/W2963881378","https://openalex.org/W2966542792","https://openalex.org/W3027201985","https://openalex.org/W3027225766","https://openalex.org/W3036453075","https://openalex.org/W3037640242","https://openalex.org/W3130754787","https://openalex.org/W3131500599","https://openalex.org/W3133630855","https://openalex.org/W3138516171","https://openalex.org/W3176330035","https://openalex.org/W3180045188","https://openalex.org/W3196107618","https://openalex.org/W4226228401","https://openalex.org/W4226305459","https://openalex.org/W4285214830","https://openalex.org/W4285276086","https://openalex.org/W4289752563","https://openalex.org/W4312549298","https://openalex.org/W4313350235","https://openalex.org/W4318767292","https://openalex.org/W4319865968","https://openalex.org/W4321021501","https://openalex.org/W4360930410","https://openalex.org/W4362653113","https://openalex.org/W4364323060","https://openalex.org/W4377079779","https://openalex.org/W4377079808","https://openalex.org/W4377139533","https://openalex.org/W4385768229","https://openalex.org/W4386071462","https://openalex.org/W4389104771","https://openalex.org/W4399449678","https://openalex.org/W6631190155","https://openalex.org/W6766978945","https://openalex.org/W6797399245","https://openalex.org/W6799457787"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2073313993"],"abstract_inverted_index":{"The":[0,205],"advancement":[1],"of":[2,11,54,60,158,194],"deep":[3],"learning":[4],"technology":[5],"has":[6],"significantly":[7],"improved":[8],"the":[9,51,120,137,156,159,171,201],"performance":[10],"high-resolution":[12],"remote":[13,175],"sensing":[14,176],"(HRRS)":[15],"image":[16],"change":[17],"detection":[18],"(CD)":[19],"task.":[20],"HRRS":[21],"images":[22],"on":[23,90,170],"CD":[24,177,186],"are":[25],"usually":[26],"captured":[27],"under":[28],"varying":[29],"conditions,":[30],"which":[31,97],"may":[32,64],"generate":[33],"pseudo-changes":[34],"caused":[35],"by":[36],"seasonal":[37],"variations,":[38],"changes":[39],"in":[40],"lighting":[41],"angles,":[42],"and":[43,83,95,106,118,143,165,174,182,197],"object":[44],"motion.":[45],"These":[46],"factors":[47],"can":[48,98],"interfere":[49],"with":[50],"effective":[52],"modeling":[53,61],"difference":[55,62,101,127,138],"information.":[56,102],"However,":[57],"conventional":[58],"methods":[59],"information":[63,139],"not":[65],"adequately":[66],"address":[67],"these":[68],"challenges,":[69],"leaving":[70],"them":[71],"susceptible":[72],"to":[73,114,134,154,161],"such":[74],"factors.":[75],"Therefore,":[76],"this":[77],"article":[78],"proposes":[79],"a":[80,104,125,146],"multiscale":[81],"alignment":[82,109],"progressive":[84,126],"feature":[85,128,148],"fusion":[86,129],"network":[87,93],"(MAPNet)":[88],"based":[89],"convolutional":[91],"neural":[92],"(CNN)":[94],"transformer,":[96],"effectively":[99],"model":[100],"First,":[103],"flow-":[105],"attention-guided":[107],"bitemporal":[108,116],"module":[110,130,150],"(FA-BAFM)":[111],"is":[112,132,152],"designed":[113],"align":[115],"features":[117],"capture":[119],"differences":[121],"between":[122],"them.":[123],"Second,":[124],"(PDFFM)":[131],"developed":[133],"comprehensively":[135],"fuse":[136],"across":[140],"various":[141],"scales":[142],"levels.":[144],"Finally,":[145],"local":[147,166],"enhancement":[149],"(LFEM)":[151],"constructed":[153],"improve":[155],"ability":[157],"backbone":[160],"extract":[162],"both":[163],"global":[164],"features.":[167],"Experimental":[168],"results":[169],"learning,":[172],"vision,":[173],"(LEVIR-CD),":[178],"Wuhan":[179],"University":[180,185],"(WHU),":[181],"Sun":[183],"Yat-Sen":[184],"(SYSU-CD)":[187],"datasets":[188],"show":[189],"that":[190],"MAPNet":[191],"achieves":[192],"F1-scores":[193],"91.90%,":[195],"94.19%,":[196],"83.69%,":[198],"respectively,":[199],"outperforming":[200],"state-of-the-art":[202],"(SOTA)":[203],"methods.":[204],"demo":[206],"code":[207],"will":[208],"be":[209],"released":[210],"athttps://github.com/zlin9/mapnet.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}