{"id":"https://openalex.org/W3131096279","doi":"https://doi.org/10.1109/tnnls.2021.3056238","title":"Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images","display_name":"Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images","publication_year":2021,"publication_date":"2021-02-20","ids":{"openalex":"https://openalex.org/W3131096279","doi":"https://doi.org/10.1109/tnnls.2021.3056238","mag":"3131096279","pmid":"https://pubmed.ncbi.nlm.nih.gov/33600325"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3056238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3056238","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5009576623","display_name":"Yue Wu","orcid":"https://orcid.org/0000-0002-3459-5079"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Wu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100707182","display_name":"Jiaheng Li","orcid":"https://orcid.org/0000-0002-1172-8000"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaheng Li","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding, Ministry of Education of China, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding, Ministry of Education of China, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090587885","display_name":"Yongzhe Yuan","orcid":"https://orcid.org/0009-0002-9206-1283"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongzhe Yuan","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006614329","display_name":"A. K. Qin","orcid":"https://orcid.org/0000-0001-6631-1651"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. K. Qin","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007404362","display_name":"Qiguang Miao","orcid":"https://orcid.org/0000-0002-2872-388X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi-Guang Miao","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091227928","display_name":"Maoguo Gong","orcid":"https://orcid.org/0000-0002-0415-8556"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mao-Guo Gong","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding, Ministry of Education of China, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding, Ministry of Education of China, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009576623"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":19.3209,"has_fulltext":false,"cited_by_count":192,"citation_normalized_percentile":{"value":0.99518745,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"33","issue":"9","first_page":"4257","last_page":"4270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12388","display_name":"Identification and Quantification in Food","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9532735347747803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7726373672485352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7182623147964478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6831650137901306},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5755642652511597},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5496255159378052},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5176916122436523},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48711156845092773},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.468860924243927},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.434596985578537},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4220130443572998},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41267579793930054}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9532735347747803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7726373672485352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7182623147964478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6831650137901306},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5755642652511597},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5496255159378052},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5176916122436523},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48711156845092773},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.468860924243927},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.434596985578537},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4220130443572998},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41267579793930054},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3056238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3056238","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33600325","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33600325","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1949608614","display_name":null,"funder_award_id":"62036006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2159723965","display_name":null,"funder_award_id":"LP180100114","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G3698760113","display_name":null,"funder_award_id":"DP200102611","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1601139921","https://openalex.org/W1959608418","https://openalex.org/W2029161185","https://openalex.org/W2036081619","https://openalex.org/W2036632898","https://openalex.org/W2050072374","https://openalex.org/W2067441435","https://openalex.org/W2070177605","https://openalex.org/W2149490731","https://openalex.org/W2165012164","https://openalex.org/W2166052353","https://openalex.org/W2221448138","https://openalex.org/W2295862745","https://openalex.org/W2320738207","https://openalex.org/W2419285013","https://openalex.org/W2497902795","https://openalex.org/W2517579290","https://openalex.org/W2519960185","https://openalex.org/W2564140372","https://openalex.org/W2606635696","https://openalex.org/W2607721373","https://openalex.org/W2760835880","https://openalex.org/W2775148801","https://openalex.org/W2779571083","https://openalex.org/W2790433324","https://openalex.org/W2809328251","https://openalex.org/W2892203832","https://openalex.org/W2894544606","https://openalex.org/W2895983303","https://openalex.org/W2900322278","https://openalex.org/W2902779903","https://openalex.org/W2902788350","https://openalex.org/W2946382053","https://openalex.org/W2965090536","https://openalex.org/W2965608468","https://openalex.org/W2966888491","https://openalex.org/W2969081030","https://openalex.org/W2979642714","https://openalex.org/W2988020997","https://openalex.org/W2997043451","https://openalex.org/W2997860833","https://openalex.org/W3010777628","https://openalex.org/W3040020917","https://openalex.org/W3105553032","https://openalex.org/W6631190155","https://openalex.org/W6640963894"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644"],"abstract_inverted_index":{"Change":[0],"detection":[1,34,140],"based":[2],"on":[3,178],"heterogeneous":[4,64,88,93],"images,":[5,14],"such":[6],"as":[7],"optical":[8],"images":[9,65,89],"and":[10,46,66,125,128],"synthetic":[11],"aperture":[12],"radar":[13],"is":[15,142],"a":[16,39,57,130,146],"challenging":[17],"problem":[18],"because":[19],"of":[20,60,83,118,159,168,172,187],"their":[21],"huge":[22],"appearance":[23],"differences.":[24],"To":[25],"combat":[26],"this":[27],"problem,":[28],"we":[29],"propose":[30],"an":[31],"unsupervised":[32],"change":[33,139],"method":[35],"that":[36],"contains":[37],"only":[38],"convolutional":[40],"autoencoder":[41,49,75,162],"(CAE)":[42],"for":[43,50],"feature":[44,70],"extraction":[45],"the":[47,77,102,112,116,138,150,156,160,166,173,184,188],"commonality":[48,74,161],"commonalities":[51],"exploration.":[52],"The":[53,72,98],"CAE":[54],"can":[55,121,133],"eliminate":[56],"large":[58],"part":[59],"redundancies":[61],"in":[62],"two":[63,87],"obtain":[67],"more":[68,108],"consistent":[69],"representations.":[71],"proposed":[73,189],"has":[76],"ability":[78],"to":[79,149],"discover":[80],"common":[81,109,119],"features":[82,110,120],"ground":[84,104],"objects":[85,105],"between":[86],"by":[90,144,165],"transforming":[91],"one":[92],"image":[94],"representation":[95],"into":[96],"another.":[97],"unchanged":[99,126,169],"regions":[100,124,170],"with":[101,192],"same":[103],"share":[106],"much":[107],"than":[111],"changed":[113,123],"regions.":[114],"Therefore,":[115],"number":[117],"indicate":[122],"regions,":[127],"then":[129],"difference":[131,151],"map":[132],"be":[134],"calculated.":[135],"At":[136],"last,":[137],"result":[141],"generated":[143],"applying":[145],"segmentation":[147],"algorithm":[148],"map.":[152],"In":[153],"our":[154],"method,":[155],"network":[157],"parameters":[158],"are":[163],"learned":[164],"relevance":[167],"instead":[171],"labels.":[174],"Our":[175],"experimental":[176],"results":[177],"five":[179],"real":[180],"data":[181],"sets":[182],"demonstrate":[183],"promising":[185],"performance":[186],"framework":[190],"compared":[191],"several":[193],"existing":[194],"approaches.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":49},{"year":2023,"cited_by_count":63},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}