{"id":"https://openalex.org/W4405934273","doi":"https://doi.org/10.1109/tgrs.2024.3524639","title":"A Copula-Guided In-Model Interpretable Neural Network for Change Detection in Heterogeneous Remote Sensing Images","display_name":"A Copula-Guided In-Model Interpretable Neural Network for Change Detection in Heterogeneous Remote Sensing Images","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405934273","doi":"https://doi.org/10.1109/tgrs.2024.3524639"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3524639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3524639","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/A5035105829","display_name":"Weiming Li","orcid":"https://orcid.org/0000-0003-1218-3687"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1218-3687","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100737123","display_name":"Xueqian Wang","orcid":"https://orcid.org/0000-0002-8632-6073"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueqian Wang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8632-6073","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438655","display_name":"Gang Li","orcid":"https://orcid.org/0000-0001-9755-2781"},"institutions":[{"id":"https://openalex.org/I32389192","display_name":"University of Alabama at Birmingham","ror":"https://ror.org/008s83205","country_code":"US","type":"education","lineage":["https://openalex.org/I32389192"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, USA"],"raw_orcid":"https://orcid.org/0000-0001-9755-2781","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, USA","institution_ids":["https://openalex.org/I32389192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065090118","display_name":"Baocheng Geng","orcid":"https://orcid.org/0000-0002-9596-0359"},"institutions":[{"id":"https://openalex.org/I32389192","display_name":"University of Alabama at Birmingham","ror":"https://ror.org/008s83205","country_code":"US","type":"education","lineage":["https://openalex.org/I32389192"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baocheng Geng","raw_affiliation_strings":["Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, USA"],"raw_orcid":"https://orcid.org/0000-0002-9596-0359","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, USA","institution_ids":["https://openalex.org/I32389192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018292481","display_name":"Pramod K. Varshney","orcid":"https://orcid.org/0000-0003-4504-5088"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pramod K. Varshney","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-4504-5088","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4348,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84898339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9952999949455261,"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":0.9952999949455261,"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/T10320","display_name":"Neural Networks and Applications","score":0.9848999977111816,"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"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.6740873456001282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6339876055717468},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5983057618141174},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5885321497917175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5217590928077698},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5008175373077393},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42975562810897827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35222160816192627},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3261656165122986},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.20500215888023376},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.12474513053894043},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11814302206039429}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.6740873456001282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6339876055717468},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5983057618141174},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5885321497917175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5217590928077698},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5008175373077393},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42975562810897827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35222160816192627},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3261656165122986},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.20500215888023376},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.12474513053894043},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11814302206039429}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3524639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3524639","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":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G7174652887","display_name":null,"funder_award_id":"62101303","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7189824073","display_name":null,"funder_award_id":"62341130","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":71,"referenced_works":["https://openalex.org/W613625395","https://openalex.org/W1965852574","https://openalex.org/W1981795482","https://openalex.org/W1995450389","https://openalex.org/W2036479590","https://openalex.org/W2056003895","https://openalex.org/W2118020555","https://openalex.org/W2118246710","https://openalex.org/W2128728535","https://openalex.org/W2135228726","https://openalex.org/W2144983735","https://openalex.org/W2158479016","https://openalex.org/W2166052353","https://openalex.org/W2167787089","https://openalex.org/W2308519059","https://openalex.org/W2344118402","https://openalex.org/W2494873755","https://openalex.org/W2564140372","https://openalex.org/W2618530766","https://openalex.org/W2627081599","https://openalex.org/W2770155885","https://openalex.org/W2779571083","https://openalex.org/W2794543231","https://openalex.org/W2889804671","https://openalex.org/W2894544606","https://openalex.org/W2899283552","https://openalex.org/W2914651367","https://openalex.org/W2921442714","https://openalex.org/W2962793481","https://openalex.org/W2962858109","https://openalex.org/W2964303497","https://openalex.org/W2969081030","https://openalex.org/W3000358529","https://openalex.org/W3015287366","https://openalex.org/W3017092406","https://openalex.org/W3033361357","https://openalex.org/W3105698493","https://openalex.org/W3134586917","https://openalex.org/W3137125108","https://openalex.org/W3158058588","https://openalex.org/W3180045188","https://openalex.org/W3182257909","https://openalex.org/W3183600011","https://openalex.org/W3184550728","https://openalex.org/W3184708347","https://openalex.org/W3194668998","https://openalex.org/W3195032332","https://openalex.org/W3196616669","https://openalex.org/W3199538063","https://openalex.org/W4213124617","https://openalex.org/W4226305459","https://openalex.org/W4240485910","https://openalex.org/W4281761935","https://openalex.org/W4282563305","https://openalex.org/W4283028368","https://openalex.org/W4312939876","https://openalex.org/W4312984702","https://openalex.org/W4313009532","https://openalex.org/W4313438466","https://openalex.org/W4319996564","https://openalex.org/W4386472823","https://openalex.org/W4387789486","https://openalex.org/W4392909631","https://openalex.org/W4398151425","https://openalex.org/W6697991780","https://openalex.org/W6731726191","https://openalex.org/W6757107679","https://openalex.org/W6790977979","https://openalex.org/W6802205045","https://openalex.org/W6838868467","https://openalex.org/W6876805775"],"related_works":["https://openalex.org/W4254184784","https://openalex.org/W2568858292","https://openalex.org/W1502836838","https://openalex.org/W2351412012","https://openalex.org/W2117969153","https://openalex.org/W2066826592","https://openalex.org/W1967916041","https://openalex.org/W1515964938","https://openalex.org/W3141866558","https://openalex.org/W1000855058"],"abstract_inverted_index":{"Change":[0],"detection":[1],"(CD)":[2],"in":[3,59,73,154],"heterogeneous":[4,23,88,94,130,166],"remote":[5],"sensing":[6],"images":[7],"has":[8,26],"been":[9],"widely":[10],"used":[11],"for":[12,87],"disaster":[13],"monitoring":[14],"and":[15,55,133,174,179,185],"land-use":[16],"management.":[17],"In":[18,105],"the":[19,22,30,38,48,53,81,108,116,126,135,145,151,155,183],"past":[20],"decade,":[21],"CD":[24,62,95],"problem":[25],"significantly":[27],"benefited":[28],"from":[29],"development":[31],"of":[32,50,57,83,111,147,149,187],"deep":[33],"neural":[34,85,101,122],"networks":[35,86],"(DNNs).":[36],"However,":[37],"purely":[39],"data-driven":[40],"DNNs":[41,58],"perform":[42],"like":[43],"a":[44,65,92,99,121],"black":[45],"box":[46],"where":[47,177],"lack":[49],"interpretability":[51,82,186],"limits":[52],"trustworthiness":[54],"controllability":[56],"most":[60],"practical":[61],"applications.":[63],"As":[64],"powerful":[66],"knowledge-driven":[67],"tool,":[68],"copula":[69,112],"theory":[70],"performs":[71],"well":[72],"modeling":[74],"dependence":[75,127,148],"among":[76],"random":[77],"variables.":[78],"To":[79],"enhance":[80],"existing":[84],"CD,":[89],"we":[90],"propose":[91],"knowledge-data-driven":[93],"method":[96],"based":[97,143],"on":[98,144,162],"copula-guided":[100],"network,":[102],"named":[103],"NN-Copula-CD.":[104],"our":[106,188],"NN-Copula-CD,":[107],"mathematical":[109],"characteristics":[110],"are":[113,138],"employed":[114],"as":[115],"loss":[117],"functions":[118],"to":[119,124],"supervise":[120],"network":[123],"learn":[125],"between":[128],"bi-temporal":[129,156],"superpixel":[131,152],"pairs,":[132],"then":[134],"changed":[136],"regions":[137],"identified":[139],"via":[140],"binary":[141],"classification":[142],"degrees":[146],"all":[150],"pairs":[153],"images.":[157],"We":[158],"conduct":[159],"in-depth":[160],"experiments":[161],"four":[163],"datasets":[164],"with":[165],"images,":[167,176],"including":[168],"synthetic":[169],"aperture":[170],"radar":[171],"(SAR),":[172],"multispectral,":[173],"near-infrared":[175],"quantitative":[178],"visual":[180],"results":[181],"demonstrate":[182],"effectiveness":[184],"proposed":[189],"NN-Copula-CD":[190],"method.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-01-01T00:00:00"}