{"id":"https://openalex.org/W2013029777","doi":"https://doi.org/10.1109/lgrs.2013.2250907","title":"Background Density Nonparametric Estimation With Data-Adaptive Bandwidths for the Detection of Anomalies in Multi-Hyperspectral Imagery","display_name":"Background Density Nonparametric Estimation With Data-Adaptive Bandwidths for the Detection of Anomalies in Multi-Hyperspectral Imagery","publication_year":2013,"publication_date":"2013-04-26","ids":{"openalex":"https://openalex.org/W2013029777","doi":"https://doi.org/10.1109/lgrs.2013.2250907","mag":"2013029777"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2013.2250907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2013.2250907","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5073606309","display_name":"Stefania Matteoli","orcid":"https://orcid.org/0000-0001-6940-9881"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Stefania Matteoli","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004320088","display_name":"Tiziana Veracini","orcid":null},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Tiziana Veracini","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064336799","display_name":"Marco Diani","orcid":"https://orcid.org/0000-0003-1520-1991"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco Diani","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089641976","display_name":"Giovanni Corsini","orcid":"https://orcid.org/0000-0002-9366-2470"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Corsini","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione, Universit\u00e0 di Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]},{"raw_affiliation_string":"Dipartimento di Ingegneria dell\u2019Informazione Universit\u00e0 di Pisa,Pisa,Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073606309"],"corresponding_institution_ids":["https://openalex.org/I108290504"],"apc_list":null,"apc_paid":null,"fwci":1.4454,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.84508565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"11","issue":"1","first_page":"163","last_page":"167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.989799976348877,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9718999862670898,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.7161649465560913},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6882139444351196},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6706611514091492},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6389375925064087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6332117915153503},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.6157974600791931},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.6100038886070251},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6024956107139587},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5879948735237122},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5837832093238831},{"id":"https://openalex.org/keywords/multivariate-kernel-density-estimation","display_name":"Multivariate kernel density estimation","score":0.5773755311965942},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5187451839447021},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5152011513710022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5147495269775391},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4679132103919983},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.41609442234039307},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3229405879974365},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3217198848724365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2957790791988373},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23763087391853333},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.17702174186706543},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.11571472883224487}],"concepts":[{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.7161649465560913},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6882139444351196},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6706611514091492},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6389375925064087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6332117915153503},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.6157974600791931},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.6100038886070251},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6024956107139587},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5879948735237122},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5837832093238831},{"id":"https://openalex.org/C84894716","wikidata":"https://www.wikidata.org/wiki/Q6935135","display_name":"Multivariate kernel density estimation","level":5,"score":0.5773755311965942},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5187451839447021},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5152011513710022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5147495269775391},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4679132103919983},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.41609442234039307},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3229405879974365},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3217198848724365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2957790791988373},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23763087391853333},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.17702174186706543},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.11571472883224487},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2013.2250907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2013.2250907","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arpi.unipi.it:11568/208392","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/document/6509402","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1970099214","https://openalex.org/W2047870694","https://openalex.org/W2050913223","https://openalex.org/W2050947749","https://openalex.org/W2077347596","https://openalex.org/W2100294832","https://openalex.org/W2124267685","https://openalex.org/W2124463804","https://openalex.org/W2129498797","https://openalex.org/W2129905273","https://openalex.org/W2140475713","https://openalex.org/W2166691113","https://openalex.org/W2167717760","https://openalex.org/W4212863985","https://openalex.org/W4233014035","https://openalex.org/W6670135276"],"related_works":["https://openalex.org/W4241010850","https://openalex.org/W3212687977","https://openalex.org/W2583877436","https://openalex.org/W2355371556","https://openalex.org/W3123419490","https://openalex.org/W2144201579","https://openalex.org/W1834385407","https://openalex.org/W2776263260","https://openalex.org/W2026307144","https://openalex.org/W4386285810"],"abstract_inverted_index":{"This":[0],"letter":[1],"presents":[2],"a":[3,11,40,69,116],"scheme":[4],"for":[5,112],"detecting":[6,113],"global":[7],"anomalies,":[8],"in":[9,20,115],"which":[10,61],"likelihood":[12],"ratio":[13],"test":[14],"based":[15],"decision":[16],"rule":[17],"is":[18,36,72],"applied":[19],"conjunction":[21],"with":[22,39,118],"an":[23],"automated":[24],"data-driven":[25],"estimation":[26,111],"of":[27,68,91,107],"the":[28,66,75,81,89,94,105],"background":[29,109],"probability":[30],"density":[31,45],"function":[32],"(PDF).":[33],"The":[34],"latter":[35],"reliably":[37],"estimated":[38],"nonparametric":[41],"variable-band":[42],"width":[43],"kernel":[44],"estimator":[46],"(VKDE),":[47],"without":[48],"making":[49],"any":[50],"distributional":[51],"assumption.":[52],"With":[53],"respect":[54,119],"to":[55,65,93,103,120],"conventional":[56,121],"fixed":[57,73],"bandwidth":[58,70],"KDE":[59],"(FKDE),":[60],"lacks":[62],"adaptivity":[63],"due":[64],"use":[67],"that":[71],"across":[74],"entire":[76],"feature":[77],"space,":[78],"VKDE":[79,108],"lets":[80],"bandwidths":[82],"adaptively":[83],"vary":[84],"pixel":[85],"by":[86],"pixel,":[87],"tailoring":[88],"amount":[90],"smoothing":[92],"local":[95],"data":[96],"density.":[97],"Two":[98],"multispectral":[99],"images":[100],"are":[101],"employed":[102],"explore":[104],"potential":[106],"PDF":[110],"anomalies":[114],"scene":[117],"nonadaptive":[122],"FKDE.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
