{"id":"https://openalex.org/W7138248333","doi":"https://doi.org/10.1609/aaai.v40i9.37665","title":"DGKAN: Dual-branch Graph Kolmogorov-Arnold Network for Unsupervised Multimodal Change Detection","display_name":"DGKAN: Dual-branch Graph Kolmogorov-Arnold Network for Unsupervised Multimodal Change Detection","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138248333","doi":"https://doi.org/10.1609/aaai.v40i9.37665"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i9.37665","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37665","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i9.37665","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129716868","display_name":"Tongfei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tongfei Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129732397","display_name":"Jianjian Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianjian Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129726527","display_name":"Tao Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129646808","display_name":"Yingbo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingbo Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129700275","display_name":"Xiaogang Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaogang Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129734030","display_name":"Zhiyong Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiyong Lv","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"9","first_page":"7278","last_page":"7286"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9879999756813049,"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":0.9879999756813049,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/consistency","display_name":"Consistency (knowledge bases)","score":0.5577999949455261},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5534999966621399},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5458999872207642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.513700008392334},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4790000021457672},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.3953000009059906},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39480000734329224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7907999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6158999800682068},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5577999949455261},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5534999966621399},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5458999872207642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.513700008392334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4790000021457672},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39160001277923584},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3257000148296356},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25760000944137573}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i9.37665","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37665","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37665","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37665","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i9.37665","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37665","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.7676149010658264,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G374887267","display_name":null,"funder_award_id":"24JK0350","funder_id":"https://openalex.org/F4320325627","funder_display_name":"Education Department of Shaanxi Province"},{"id":"https://openalex.org/G4461106617","display_name":null,"funder_award_id":"23JP014","funder_id":"https://openalex.org/F4320325627","funder_display_name":"Education Department of Shaanxi Province"},{"id":"https://openalex.org/G4502311844","display_name":null,"funder_award_id":"23JP022","funder_id":"https://openalex.org/F4320325627","funder_display_name":"Education Department of Shaanxi Province"},{"id":"https://openalex.org/G594039107","display_name":null,"funder_award_id":"62201334","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6103957959","display_name":null,"funder_award_id":"2024GX-YBXM-121","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"},{"id":"https://openalex.org/G7996973796","display_name":null,"funder_award_id":"62271296","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/F4320325627","display_name":"Education Department of Shaanxi Province","ror":null},{"id":"https://openalex.org/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0,52],"change":[1],"detection":[2],"(MCD)":[3],"has":[4],"important":[5],"applications":[6],"in":[7,147],"disaster":[8],"assessment,":[9],"but":[10],"the":[11,35,46,105,110,145,159,172,183,186],"nonlinear":[12,75],"distortion":[13],"of":[14,117,162,185],"features":[15,50,96,130,152],"and":[16,73,97,121,179,188],"spatial":[17,70],"misalignment":[18],"caused":[19],"by":[20,44,155],"sensor":[21],"imaging":[22],"differences":[23],"make":[24],"it":[25],"difficult":[26],"to":[27,41,68,101,112,125],"obtain":[28],"changes":[29],"through":[30,131],"direct":[31],"comparison.":[32],"To":[33,57],"overcome":[34],"above":[36],"problems,":[37],"this":[38],"study":[39],"aims":[40],"realize":[42],"MCD":[43,168],"capturing":[45],"modality-independent":[47],"structural":[48,71,94,128,150],"commonality":[49,95,129,151],"between":[51,153],"Remote":[53],"Sensing":[54],"Images":[55],"(MRSIs).":[56],"achieve":[58,176],"this,":[59,80],"we":[60,81,135],"devise":[61],"a":[62,83,118,137],"basic":[63],"Graph":[64],"Kolmogorov-Arnold":[65],"Network":[66],"(GKAN)":[67],"excavate":[69],"relationships":[72],"cross-modal":[74,163],"mappings":[76],"simultaneously.":[77],"Based":[78],"on":[79,158,166],"propose":[82],"Dual-branch":[84],"GKAN":[85,106,187],"(DGKAN)":[86],"for":[87],"unsupervised":[88,156],"MCD,":[89],"which":[90,143],"can":[91,175],"capture":[92],"spatial-spectral":[93,127,149],"compare":[98],"them":[99],"directly":[100],"detect":[102],"changes.":[103],"Concretely,":[104],"is":[107],"used":[108],"within":[109],"DGKAN":[111,174],"build":[113],"two":[114,122],"autoencoders":[115],"consisting":[116],"Siamese":[119],"encoder":[120],"independent":[123],"decoders":[124],"learn":[126],"feature":[132],"reconstruction.":[133],"Besides,":[134],"introduce":[136],"Covariance":[138],"Structural":[139],"Commonality":[140],"Loss":[141],"(CSCL),":[142],"guides":[144],"network":[146],"extracting":[148],"MRSIs":[154],"constraints":[157],"distributional":[160],"consistency":[161],"features.":[164],"Experiments":[165],"several":[167],"datasets":[169],"show":[170],"that":[171],"proposed":[173],"convincing":[177],"results,":[178],"ablation":[180],"studies":[181],"verify":[182],"effectiveness":[184],"CSCL.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}