{"id":"https://openalex.org/W2041292962","doi":"https://doi.org/10.1109/igarss.2014.6946706","title":"A novel neural approach for unsupervised change detection using SOM clustering for pseudo-training set selection followed by CSOM classifier","display_name":"A novel neural approach for unsupervised change detection using SOM clustering for pseudo-training set selection followed by CSOM classifier","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2041292962","doi":"https://doi.org/10.1109/igarss.2014.6946706","mag":"2041292962"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2014.6946706","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6946706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5068538427","display_name":"Victor Neagoe","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":true,"raw_author_name":"Victor Neagoe","raw_affiliation_strings":["Department of Applied Electronics and Information Engineering, \u201cPolitehnica\u201d University of Bucharest, Romania","[Department of Applied Electronics and Information Engineering, Politehnica University of Bucharest, Romania]"],"affiliations":[{"raw_affiliation_string":"Department of Applied Electronics and Information Engineering, \u201cPolitehnica\u201d University of Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]},{"raw_affiliation_string":"[Department of Applied Electronics and Information Engineering, Politehnica University of Bucharest, Romania]","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108452194","display_name":"Alexandru Ciurea","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":"Alexandru Ciurea","raw_affiliation_strings":["Department of Applied Electronics and Information Engineering, \u201cPolitehnica\u201d University of Bucharest, Romania","[Department of Applied Electronics and Information Engineering, Politehnica University of Bucharest, Romania]"],"affiliations":[{"raw_affiliation_string":"Department of Applied Electronics and Information Engineering, \u201cPolitehnica\u201d University of Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]},{"raw_affiliation_string":"[Department of Applied Electronics and Information Engineering, Politehnica University of Bucharest, Romania]","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Italy","Department of Inf. Engineering and Computer Science, University of Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Inf. Engineering and Computer Science, University of Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087668203","display_name":"Francesca Bovolo","orcid":"https://orcid.org/0000-0003-3104-7656"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesca Bovolo","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Italy","Department of Inf. Engineering and Computer Science, University of Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Inf. Engineering and Computer Science, University of Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068538427"],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":1.3797,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.84277152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"30","issue":null,"first_page":"1437","last_page":"1440"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9958000183105469,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9929999709129333,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7015513181686401},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6969174146652222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6654067039489746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6510469913482666},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5911673903465271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5239372849464417},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.4933001399040222},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4900704622268677},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.43955564498901367},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43436992168426514},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34676724672317505},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18791207671165466}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7015513181686401},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6969174146652222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6654067039489746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6510469913482666},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5911673903465271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5239372849464417},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.4933001399040222},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4900704622268677},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.43955564498901367},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43436992168426514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34676724672317505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18791207671165466}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2014.6946706","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6946706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/99341","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/99341","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2036798369","https://openalex.org/W2049633694","https://openalex.org/W2052514956","https://openalex.org/W2102738574","https://openalex.org/W2104374858","https://openalex.org/W2118116484","https://openalex.org/W2140023211","https://openalex.org/W2153864221","https://openalex.org/W2160544350","https://openalex.org/W2161161768","https://openalex.org/W2165577558","https://openalex.org/W2482549452","https://openalex.org/W4212863985","https://openalex.org/W4213332169","https://openalex.org/W7048738093"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W62810557","https://openalex.org/W4388409104","https://openalex.org/W1544811710","https://openalex.org/W1511643196","https://openalex.org/W3005969065","https://openalex.org/W2005234362","https://openalex.org/W2162970382","https://openalex.org/W1997235926"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,89,95,104,124,168],"novel":[4],"neural":[5,138],"model":[6,85,147],"for":[7,25,116],"unsupervised":[8],"change":[9],"detection":[10],"in":[11],"time":[12],"series":[13],"of":[14,47,55,112,118,136,144],"multispectral":[15],"remote":[16],"sensing":[17],"imagery":[18],"using":[19,88],"clustering":[20,62],"with":[21,32,123],"Self-Organizing":[22,34],"Map":[23],"(SOM)":[24],"automatic":[26],"pseudo-training":[27,73,119],"sample":[28,74,120],"set":[29,75,92,121],"selection":[30,117],"cascaded":[31],"Concurrent":[33],"Maps":[35],"(CSOM)":[36],"classifier.":[37,130],"The":[38,84,131],"proposed":[39,146],"algorithm":[40,115],"has":[41],"the":[42,53,66,72,109,134,141,145,149],"following":[43],"steps:":[44],"(a)":[45],"computation":[46],"difference":[48],"image":[49,91],"(DI)":[50],"corresponding":[51],"to":[52,63],"magnitudes":[54],"Spectral":[56],"Change":[57],"Vectors":[58],"(SCVs);":[59],"(b)":[60],"SOM":[61],"automatically":[64],"deduce":[65],"SCV":[67],"domain":[68],"quantization":[69],"parameters":[70],"defining":[71],"regions":[76],"(changed,":[77],"unchanged":[78],"and":[79,99,165],"uncertain);":[80],"(c)":[81],"CSOM":[82],"classification.":[83],"is":[86,152],"evaluated":[87],"Landsat-5":[90],"acquired":[93],"on":[94],"Mexico":[96],"area":[97],"before":[98],"after":[100],"two":[101],"wildfires.":[102],"As":[103],"benchmark,":[105],"we":[106],"have":[107],"considered":[108],"classical":[110,150],"method":[111],"Bayes":[113],"theory-EM":[114],"combined":[122],"S":[125],"<sup":[126],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[127],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>":[128],"VM":[129],"results":[132],"confirm":[133],"effectiveness":[135],"our":[137],"approach.":[139],"Moreover,":[140],"exciting":[142],"advantage":[143],"over":[148],"ones":[151],"that":[153],"it":[154,166],"does":[155],"not":[156],"require":[157],"any":[158],"statistical":[159],"assumptions":[160],"regarding":[161],"changed/unchanged":[162],"SCVs":[163],"data":[164],"implies":[167],"reduced":[169],"computational":[170],"effort.":[171]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
