{"id":"https://openalex.org/W3162150919","doi":"https://doi.org/10.1109/icpr48806.2021.9412644","title":"The eXPose Approach to Crosslier Detection","display_name":"The eXPose Approach to Crosslier Detection","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162150919","doi":"https://doi.org/10.1109/icpr48806.2021.9412644","mag":"3162150919"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3655544/view","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062840797","display_name":"Ant\u00f3nio Pereira Barata","orcid":null},"institutions":[{"id":"https://openalex.org/I331567899","display_name":"Ministry of Infrastructure and Water Management","ror":"https://ror.org/056a6x975","country_code":"NL","type":"government","lineage":["https://openalex.org/I331567899","https://openalex.org/I4210140876"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Antonio Pereira Barata","raw_affiliation_strings":["Ministry of Infrastructure and Water Management, ILT, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Infrastructure and Water Management, ILT, the Netherlands","institution_ids":["https://openalex.org/I331567899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032475130","display_name":"Frank W. Takes","orcid":"https://orcid.org/0000-0001-5468-1030"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Frank W. Takes","raw_affiliation_strings":["LIACS, Leiden University, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LIACS, Leiden University, the Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054345881","display_name":"H.J. van den Herik","orcid":"https://orcid.org/0000-0001-9751-761X"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"H. Jaap van den Herik","raw_affiliation_strings":["LCDS, Leiden University, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LCDS, Leiden University, the Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013179642","display_name":"Cor J. Veenman","orcid":"https://orcid.org/0000-0002-2645-1198"},"institutions":[{"id":"https://openalex.org/I148297040","display_name":"Netherlands Organisation for Applied Scientific Research","ror":"https://ror.org/01bnjb948","country_code":"NL","type":"nonprofit","lineage":["https://openalex.org/I148297040"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Cor J. Veenman","raw_affiliation_strings":["TNO, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TNO, the Netherlands","institution_ids":["https://openalex.org/I148297040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1399,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53536701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2312","last_page":"2319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9869999885559082,"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/T11220","display_name":"Water Systems and Optimization","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/computer-science","display_name":"Computer science","score":0.7699097990989685},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6979381442070007},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.612987220287323},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5480957627296448},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5000922679901123},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.49823498725891113},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4929797649383545},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4890064001083374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43909451365470886},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4260265827178955},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14119359850883484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699097990989685},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6979381442070007},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.612987220287323},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5480957627296448},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5000922679901123},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.49823498725891113},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4929797649383545},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4890064001083374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43909451365470886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4260265827178955},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14119359850883484},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3655543","is_oa":true,"landing_page_url":"https://hdl.handle.net/1887/3655543","pdf_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3655544/view","source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"Article in monograph or in proceedings"},{"id":"pmh:oai:oai-pmh.tno.nl:68083","is_oa":false,"landing_page_url":"https://resolver.tno.nl/uuid:68b3c692-7947-45ef-a42e-b8834c071b6d","pdf_url":null,"source":{"id":"https://openalex.org/S7407055233","display_name":"TNO Repository","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3655543","is_oa":true,"landing_page_url":"https://hdl.handle.net/1887/3655543","pdf_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3655544/view","source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"Article in monograph or in proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320329609","display_name":"Ministry of Infrastructure and Water Management","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3162150919.pdf","grobid_xml":"https://content.openalex.org/works/W3162150919.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W593934247","https://openalex.org/W1487271345","https://openalex.org/W1501262304","https://openalex.org/W1618905105","https://openalex.org/W1678356000","https://openalex.org/W1963509088","https://openalex.org/W1963565057","https://openalex.org/W1974879849","https://openalex.org/W1976331960","https://openalex.org/W1982304603","https://openalex.org/W1993144410","https://openalex.org/W1995443851","https://openalex.org/W2039088136","https://openalex.org/W2077442291","https://openalex.org/W2097998348","https://openalex.org/W2112081648","https://openalex.org/W2127251289","https://openalex.org/W2132862423","https://openalex.org/W2140187489","https://openalex.org/W2140404878","https://openalex.org/W2144182447","https://openalex.org/W2159241419","https://openalex.org/W2166403701","https://openalex.org/W2170712852","https://openalex.org/W2171286664","https://openalex.org/W2192128865","https://openalex.org/W2212194823","https://openalex.org/W2219861784","https://openalex.org/W2295598076","https://openalex.org/W2296719434","https://openalex.org/W2298871042","https://openalex.org/W2523239021","https://openalex.org/W2586297576","https://openalex.org/W2591700809","https://openalex.org/W2731977498","https://openalex.org/W2760506815","https://openalex.org/W2782761346","https://openalex.org/W2794075952","https://openalex.org/W2795357172","https://openalex.org/W2795514556","https://openalex.org/W2795599393","https://openalex.org/W2909682623","https://openalex.org/W2925507233","https://openalex.org/W2938292019","https://openalex.org/W2989746935","https://openalex.org/W2991735283","https://openalex.org/W3102476541","https://openalex.org/W4230674625","https://openalex.org/W4237247744","https://openalex.org/W4254182148","https://openalex.org/W6636501900","https://openalex.org/W6674385629","https://openalex.org/W6730092156"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Transit":[0],"of":[1,14,26,115,120,180],"wasteful":[2],"materials":[3],"within":[4],"the":[5,23,113,145,177],"European":[6],"Union":[7],"is":[8,45,76],"highly":[9],"regulated":[10],"through":[11],"a":[12,27,33,68,121,131,148],"system":[13],"permits.":[15],"Waste":[16],"processing":[17],"costs":[18],"vary":[19],"greatly":[20],"depending":[21],"on":[22,73,138],"waste":[24,39],"category":[25,103,122,140],"permit.":[28],"Therefore,":[29],"companies":[30],"may":[31],"have":[32],"financial":[34],"incentive":[35],"to":[36,46,65,134,156],"allege":[37],"transporting":[38],"with":[40,172],"erroneous":[41],"categorisation.":[42],"Our":[43],"goal":[44],"assist":[47],"inspectors":[48],"in":[49,97,101,168,183],"selecting":[50],"potentially":[51],"manipulated":[52],"permits":[53],"for":[54,153],"further":[55],"investigation,":[56],"making":[57],"their":[58],"task":[59],"more":[60],"effective":[61],"and":[62,86,104,142,175],"efficient.":[63],"Due":[64],"data":[66,87],"limitations,":[67],"supervised":[69,139],"learning":[70],"approach":[71,133],"based":[72,137],"historical":[74],"cases":[75],"not":[77,91],"possible.":[78],"Standard":[79],"unsupervised":[80],"approaches,":[81],"such":[82],"as":[83],"outlier":[84,165],"detection":[85,136,166],"quality-assurance":[88],"techniques,":[89],"are":[90,95],"suited":[92],"since":[93],"we":[94,110],"interested":[96],"targeting":[98,184],"non-random":[99],"modifications":[100],"both":[102],"category-correlated":[105],"features.":[106],"For":[107],"this":[108],"purpose":[109],"(1)":[111],"introduce":[112],"concept":[114],"crosslier:":[116],"an":[117],"anomalous":[118],"instance":[119],"which":[123],"lies":[124],"across":[125],"other":[126],"categories;":[127],"(2)":[128],"propose":[129],"eXPose:":[130],"novel":[132],"crosslier":[135,146],"modelling;":[141],"(3)":[143],"present":[144],"diagram:":[147],"visualisation":[149],"tool":[150],"specifically":[151],"designed":[152],"domain":[154],"experts":[155],"easily":[157],"assess":[158],"crossliers.":[159],"We":[160],"compare":[161],"eXPose":[162],"against":[163],"traditional":[164],"methods":[167],"various":[169],"benchmark":[170],"datasets":[171],"synthetic":[173],"crossliers":[174],"show":[176],"superior":[178],"performance":[179],"our":[181],"method":[182],"these":[185],"instances.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2021-05-24T00:00:00"}
