{"id":"https://openalex.org/W4296209273","doi":"https://doi.org/10.1109/tgrs.2022.3207311","title":"Hybrid DNN-Dirichlet Anomaly Detection and Ranking: Case of Burned Areas Discovery","display_name":"Hybrid DNN-Dirichlet Anomaly Detection and Ranking: Case of Burned Areas Discovery","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296209273","doi":"https://doi.org/10.1109/tgrs.2022.3207311"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3207311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3207311","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/A5021376776","display_name":"Mihai Coca","orcid":"https://orcid.org/0000-0003-2434-7554"},"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":"Mihai Coca","raw_affiliation_strings":["Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0003-2434-7554","affiliations":[{"raw_affiliation_string":"Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071755123","display_name":"Iulia Coca Neagoe","orcid":"https://orcid.org/0000-0001-9902-2071"},"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":"Iulia Coca Neagoe","raw_affiliation_strings":["Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0001-9902-2071","affiliations":[{"raw_affiliation_string":"Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032370631","display_name":"Mihai Datcu","orcid":"https://orcid.org/0000-0002-3477-9687"},"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":"Mihai Datcu","raw_affiliation_strings":["Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0002-3477-9687","affiliations":[{"raw_affiliation_string":"Research Center for Spatial Information (CEOSpaceTech), Politehnica University of Bucharest (UPB), Bucharest, Romania","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":1.3168,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.82334869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"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":0.9961000084877014,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9927999973297119,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9617999792098999,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.714856743812561},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.656069278717041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5450140237808228},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5121104717254639},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5046297311782837},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4163576662540436},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.41124480962753296},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3962267339229584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35603222250938416},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1502060890197754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.714856743812561},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.656069278717041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5450140237808228},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5121104717254639},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5046297311782837},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4163576662540436},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.41124480962753296},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3962267339229584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35603222250938416},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1502060890197754},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3207311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3207311","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":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W190008395","https://openalex.org/W1976526581","https://openalex.org/W1980058571","https://openalex.org/W2000188520","https://openalex.org/W2043380577","https://openalex.org/W2077509829","https://openalex.org/W2105497548","https://openalex.org/W2108890220","https://openalex.org/W2112884102","https://openalex.org/W2115568725","https://openalex.org/W2128859735","https://openalex.org/W2133059825","https://openalex.org/W2144221002","https://openalex.org/W2194775991","https://openalex.org/W2204904589","https://openalex.org/W2205875912","https://openalex.org/W2476045487","https://openalex.org/W2559468428","https://openalex.org/W2579903706","https://openalex.org/W2769358239","https://openalex.org/W2784032999","https://openalex.org/W2786599352","https://openalex.org/W2807984376","https://openalex.org/W2887685367","https://openalex.org/W2905880828","https://openalex.org/W2913939497","https://openalex.org/W2920767026","https://openalex.org/W2965716428","https://openalex.org/W2986943971","https://openalex.org/W2990822052","https://openalex.org/W2997167991","https://openalex.org/W3003808604","https://openalex.org/W3007718445","https://openalex.org/W3029679819","https://openalex.org/W3045606376","https://openalex.org/W3092261202","https://openalex.org/W3112898771","https://openalex.org/W3115950764","https://openalex.org/W3136985093","https://openalex.org/W3152793483","https://openalex.org/W3165730205","https://openalex.org/W3189108671","https://openalex.org/W3207827241","https://openalex.org/W4200044643","https://openalex.org/W4205319111","https://openalex.org/W4230960895","https://openalex.org/W4388297464","https://openalex.org/W6607826182","https://openalex.org/W6684957177","https://openalex.org/W6728622933","https://openalex.org/W6748865747","https://openalex.org/W6752745768"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W1544811710","https://openalex.org/W2124951708","https://openalex.org/W172072032","https://openalex.org/W2006066416","https://openalex.org/W3157073418","https://openalex.org/W2039041387","https://openalex.org/W2032891171"],"abstract_inverted_index":{"In":[0,47],"the":[1,31,37,44,104,131,143,148,151,172,188,226],"past":[2],"decade,":[3],"anomaly":[4,134],"detection":[5,164],"has":[6],"experienced":[7],"an":[8,52],"expanding":[9],"attraction":[10],"in":[11,22,60,78,110,135,219,234],"satellite":[12],"data":[13,120,136],"analysis.":[14],"Monitoring":[15],"wildfire":[16],"dynamics":[17],"plays":[18],"a":[19,65,69,75,84,91,126,155],"substantial":[20,227],"part":[21],"global":[23],"land":[24],"management,":[25],"i.e.,":[26,207],"to":[27,88,102,124,211],"detect":[28],"and":[29,42,121,175,200,228],"determine":[30],"expansion":[32],"of":[33,39,93,106,133,150,158,231],"such":[34],"areas,":[35],"estimate":[36],"deterioration":[38],"forest":[40],"regions,":[41],"assist":[43],"intervention":[45],"plan.":[46],"this":[48],"paper,":[49],"we":[50],"proposed":[51,152],"approach":[53],"for":[54],"Sentinel-2":[55,205],"scenes":[56],"that":[57,129],"detects":[58],"anomalies":[59,233],"burned":[61,203],"area":[62,204],"contexts":[63],"using":[64],"rank-ordered":[66],"method":[67,153],"on":[68,138,154,195],"single":[70],"post-event":[71],"image.":[72],"We":[73,146,217],"adopted":[74],"self-supervised":[76],"paradigm":[77],"learning":[79],"image":[80],"representations":[81],"by":[82,142],"training":[83,173,189],"deep":[85],"convolutional":[86],"model":[87],"differentiate":[89],"between":[90],"series":[92],"geometric":[94],"transformations.":[95],"Dirichlet":[96,113],"distributions":[97],"are":[98,116,122],"selected":[99],"as":[100],"priors":[101],"characterize":[103],"variability":[105],"random":[107],"multinomial":[108],"distribution":[109],"multispectral":[111,235],"data.":[112,236],"precision":[114],"parameters":[115],"computed":[117],"from":[118,183,208],"observed":[119],"used":[123],"construct":[125],"ranking":[127],"function":[128],"quantifies":[130],"degree":[132],"based":[137],"softmax":[139],"responses":[140],"given":[141],"trained":[144],"classifier.":[145],"evaluated":[147],"performance":[149],"cumulative":[156],"effort":[157],"two":[159,201],"remote":[160],"sensing":[161],"tasks,":[162],"open-set":[163],"(i.e.,":[165,178],"test":[166,179,221],"datasets":[167,180,222],"contain":[168],"classes":[169],"unseen":[170],"at":[171],"time)":[174],"location":[176,186],"separation":[177],"include":[181],"images":[182],"distinct":[184],"spatial":[185],"than":[187],"images).":[190],"The":[191],"experiments":[192],"were":[193],"performed":[194],"three":[196],"different":[197],"datasets,":[198,206],"BigEarthNet":[199],"actual":[202],"predisposed":[209],"zones":[210],"fire":[212],"events,":[213],"Australia,":[214],"respectively":[215],"Bolivia.":[216],"retained":[218],"all":[220],"state-of-the-art":[223],"performance,":[224],"considering":[225],"diversified":[229],"types":[230],"natural":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}