{"id":"https://openalex.org/W2564140372","doi":"https://doi.org/10.1109/tnnls.2016.2636227","title":"A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images","display_name":"A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images","publication_year":2016,"publication_date":"2016-12-22","ids":{"openalex":"https://openalex.org/W2564140372","doi":"https://doi.org/10.1109/tnnls.2016.2636227","mag":"2564140372","pmid":"https://pubmed.ncbi.nlm.nih.gov/28026789"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2016.2636227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2636227","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":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/A_Deep_Convolutional_Coupling_Network_for_Change_Detection_Based_on_Heterogeneous_Optical_and_Radar_Images/27514269","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100625089","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0002-5999-2361"},"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":"Jia Liu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","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":"Maoguo Gong","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-0415-8556","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, 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/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kai Qin","raw_affiliation_strings":["School of Computer Science and Information Technology, RMIT University, Melbourne, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Technology, RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007173759","display_name":"Puzhao Zhang","orcid":"https://orcid.org/0000-0001-9907-0989"},"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":"Puzhao Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.5906,"has_fulltext":false,"cited_by_count":513,"citation_normalized_percentile":{"value":0.9945987,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"29","issue":"3","first_page":"545","last_page":"559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9927999973297119,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9914000034332275,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7614996433258057},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7069937586784363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.676705002784729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6192641854286194},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5814820528030396},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5687627196311951},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5114240050315857},{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.4406951367855072},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4164540767669678},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3414720594882965},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.328066349029541},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28530585765838623},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11949929594993591},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0891788899898529},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07036447525024414}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7614996433258057},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7069937586784363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.676705002784729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6192641854286194},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5814820528030396},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5687627196311951},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5114240050315857},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.4406951367855072},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4164540767669678},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3414720594882965},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.328066349029541},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28530585765838623},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11949929594993591},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0891788899898529},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07036447525024414},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tnnls.2016.2636227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2636227","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:28026789","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28026789","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},{"id":"pmh:oai:alma.61RMIT_INST:11247985940001341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/TNNLS.2016.2636227","pdf_url":null,"source":{"id":"https://openalex.org/S4306402074","display_name":"RMIT Research Repository (RMIT University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82951845","host_organization_name":"RMIT University","host_organization_lineage":["https://openalex.org/I82951845"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/27514269","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Deep_Convolutional_Coupling_Network_for_Change_Detection_Based_on_Heterogeneous_Optical_and_Radar_Images/27514269","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:researchbank.swinburne.edu.au:49bda8b9-7e79-4248-a7a8-86db9c052b9a/1","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.3/438145","pdf_url":null,"source":{"id":"https://openalex.org/S4306401157","display_name":"Swinburne Research Bank (Swinburne University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I57093077","host_organization_name":"Swinburne University of Technology","host_organization_lineage":["https://openalex.org/I57093077"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems, Vol. 29, no. 3 (2016), pp. 545-559","raw_type":null}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/27514269","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Deep_Convolutional_Coupling_Network_for_Change_Detection_Based_on_Heterogeneous_Optical_and_Radar_Images/27514269","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3057425273","display_name":null,"funder_award_id":"20130203110011","funder_id":"https://openalex.org/F4320336024","funder_display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China"},{"id":"https://openalex.org/G5000516249","display_name":null,"funder_award_id":"61422209","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"},{"id":"https://openalex.org/F4320336024","display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1601139921","https://openalex.org/W1964069486","https://openalex.org/W1964967908","https://openalex.org/W1965126626","https://openalex.org/W1965766334","https://openalex.org/W1972731536","https://openalex.org/W1997534118","https://openalex.org/W1998595580","https://openalex.org/W2007584825","https://openalex.org/W2025768430","https://openalex.org/W2026665610","https://openalex.org/W2029161185","https://openalex.org/W2030728252","https://openalex.org/W2034073840","https://openalex.org/W2036798369","https://openalex.org/W2050072374","https://openalex.org/W2054085770","https://openalex.org/W2063756240","https://openalex.org/W2067441435","https://openalex.org/W2069522573","https://openalex.org/W2069747869","https://openalex.org/W2070813603","https://openalex.org/W2085625911","https://openalex.org/W2110519070","https://openalex.org/W2110798204","https://openalex.org/W2111560116","https://openalex.org/W2111787810","https://openalex.org/W2112796928","https://openalex.org/W2118116484","https://openalex.org/W2126176832","https://openalex.org/W2130020884","https://openalex.org/W2131307323","https://openalex.org/W2133257461","https://openalex.org/W2135228726","https://openalex.org/W2136922672","https://openalex.org/W2138055993","https://openalex.org/W2140235830","https://openalex.org/W2140619591","https://openalex.org/W2144615653","https://openalex.org/W2145094598","https://openalex.org/W2146954163","https://openalex.org/W2149490731","https://openalex.org/W2151137405","https://openalex.org/W2152185773","https://openalex.org/W2163922914","https://openalex.org/W2166052353","https://openalex.org/W2170140722","https://openalex.org/W2170260354","https://openalex.org/W2170947705","https://openalex.org/W2174636480","https://openalex.org/W2218318129","https://openalex.org/W2221448138","https://openalex.org/W2515342364","https://openalex.org/W2919115771","https://openalex.org/W2997574889","https://openalex.org/W3196803037","https://openalex.org/W6676481782","https://openalex.org/W6679718588","https://openalex.org/W6681096077","https://openalex.org/W6688386640","https://openalex.org/W6725711919","https://openalex.org/W6800561134"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2730764323","https://openalex.org/W3123806511","https://openalex.org/W2164995725"],"abstract_inverted_index":{"We":[0],"propose":[1],"an":[2,47],"unsupervised":[3],"deep":[4],"convolutional":[5,68],"coupling":[6,72,130],"network":[7,59,123,165],"for":[8],"change":[9,27,51,143],"detection":[10,28,52,115,144],"based":[11,31,53,146],"on":[12,22,32,54,147,152],"two":[13,75,81],"heterogeneous":[14,55,148,156],"images":[15,77,157],"acquired":[16],"by":[17,117,127],"optical":[18,41],"sensors":[19],"and":[20,42,70,155],"radars":[21],"different":[23,105,139],"dates.":[24],"Most":[25],"existing":[26,142,169],"methods":[29,145],"are":[30,87,125],"homogeneous":[33],"images.":[34,56,149],"Due":[35],"to":[36,112],"the":[37,80,84,104,113,159,163],"complementary":[38],"properties":[39],"of":[40,66,83,162],"radar":[43],"sensors,":[44],"there":[45],"is":[46,60,107,135,138],"increasing":[48],"interest":[49],"in":[50],"The":[57,74,122,132],"proposed":[58,164],"symmetric":[61],"with":[62,79,167],"each":[63],"side":[64],"consisting":[65],"one":[67],"layer":[69],"several":[71,168],"layers.":[73],"input":[76],"connected":[78],"sides":[82],"network,":[85],"respectively,":[86],"transformed":[88],"into":[89],"a":[90,119,129],"feature":[91,95,102],"space":[92],"where":[93],"their":[94],"representations":[96],"become":[97],"more":[98],"consistent.":[99],"In":[100],"this":[101],"space,":[103],"map":[106,116],"calculated,":[108],"which":[109,137],"then":[110],"leads":[111],"ultimate":[114],"applying":[118],"thresholding":[120],"algorithm.":[121],"parameters":[124],"learned":[126],"optimizing":[128],"function.":[131],"learning":[133],"process":[134],"unsupervised,":[136],"from":[140],"most":[141],"Experimental":[150],"results":[151],"both":[153],"homogenous":[154],"demonstrate":[158],"promising":[160],"performance":[161],"compared":[166],"approaches.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":26},{"year":2025,"cited_by_count":58},{"year":2024,"cited_by_count":92},{"year":2023,"cited_by_count":60},{"year":2022,"cited_by_count":75},{"year":2021,"cited_by_count":65},{"year":2020,"cited_by_count":60},{"year":2019,"cited_by_count":50},{"year":2018,"cited_by_count":20},{"year":2017,"cited_by_count":7}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2025-10-10T00:00:00"}