{"id":"https://openalex.org/W4313072346","doi":"https://doi.org/10.1109/igarss46834.2022.9884513","title":"Convolutional Neural Network-Based Fractal Coding Method for Image Translation in Multimodal Change Detection","display_name":"Convolutional Neural Network-Based Fractal Coding Method for Image Translation in Multimodal Change Detection","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4313072346","doi":"https://doi.org/10.1109/igarss46834.2022.9884513"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884513","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5091483225","display_name":"Anamaria R\u0103doi","orcid":"https://orcid.org/0000-0002-7577-1067"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Anamaria Radoi","raw_affiliation_strings":["University Politehnica of Bucharest"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009867861","display_name":"Melisa \u00dcnsalan","orcid":null},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Melisa Unsalan","raw_affiliation_strings":["University Politehnica of Bucharest"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":0.3567,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58641284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1063","last_page":"1066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983000159263611,"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":0.9983000159263611,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8039403557777405},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7259682416915894},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6430281400680542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6245947480201721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5325725674629211},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5158218741416931},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4110877811908722}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039403557777405},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7259682416915894},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6430281400680542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6245947480201721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5325725674629211},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5158218741416931},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4110877811908722},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884513","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4758328218","display_name":null,"funder_award_id":"PN-III-P1-1.1-PD-2019-0843 (MDM-SITS)","funder_id":"https://openalex.org/F4320324070","funder_display_name":"Ministry of Education and Research, Romania"}],"funders":[{"id":"https://openalex.org/F4320324070","display_name":"Ministry of Education and Research, Romania","ror":"https://ror.org/00dh5gw98"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1702904403","https://openalex.org/W2037693374","https://openalex.org/W2097921974","https://openalex.org/W2146954163","https://openalex.org/W2160544350","https://openalex.org/W2766372927","https://openalex.org/W2779571083","https://openalex.org/W2786977213","https://openalex.org/W2790433324","https://openalex.org/W2968065858","https://openalex.org/W2969081030","https://openalex.org/W2970302645","https://openalex.org/W3022569728","https://openalex.org/W4249775755","https://openalex.org/W4287814820","https://openalex.org/W6631190155","https://openalex.org/W6674878074","https://openalex.org/W6748692466"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W4293226380","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W4390516098","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2181948922"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,142],"data":[2],"is":[3,61,105,116,121],"characterized":[4],"by":[5],"a":[6,64,71,83,90,108],"large":[7],"degree":[8],"of":[9,41,73,75,139,147],"heterogeneity":[10],"and":[11,27,36,57],"variability.":[12],"In":[13,45],"this":[14,46],"context,":[15],"change":[16,119],"detection":[17],"in":[18,30],"heterogeneous":[19,140],"bitemporal":[20],"satellite":[21],"images":[22,143],"has":[23],"become":[24],"an":[25,50,124],"emerging":[26],"important":[28,43],"topic":[29],"order":[31],"to":[32,37,153],"ensure":[33],"monitoring":[34],"continuity":[35],"reduce":[38],"the":[39,55,94,100,112,118,145,148],"probability":[40],"missing":[42],"events.":[44],"paper,":[47],"we":[48],"propose":[49],"image":[51,113],"translation":[52,115],"method":[53],"between":[54,93],"pre-event":[56],"post-event":[58],"modalities":[59],"that":[60,69],"based":[62],"on":[63],"modified":[65],"fractal":[66],"coding":[67],"technique":[68],"determines":[70],"dictionary":[72],"locations":[74],"self-similar":[76,103],"structures.":[77],"Self-similar":[78],"structures":[79,104],"are":[80],"identified":[81],"using":[82,107],"convolutional":[84],"neural":[85],"network":[86],"(CNN)":[87],"encoder":[88],"as":[89],"mapping":[91],"function":[92],"compressed":[95],"representations.":[96],"The":[97,133],"search":[98],"for":[99],"k":[101],"closest":[102],"performed":[106],"vantage-point":[109],"tree.":[110],"Once":[111],"modality":[114],"performed,":[117],"map":[120],"obtained":[122],"via":[123],"unsupervised":[125],"Expectation-Maximization":[126],"(EM)":[127],"approach":[128],"with":[129],"spatial":[130],"context":[131],"constraints.":[132],"experiments":[134],"conducted":[135],"over":[136],"several":[137],"pairs":[138],"remote":[141],"show":[144],"effectiveness":[146],"proposed":[149,155],"technique,":[150],"if":[151],"compared":[152],"other":[154],"methods.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
