{"id":"https://openalex.org/W2127013183","doi":"https://doi.org/10.1109/icsmc.2008.4811834","title":"Robust regression to varying data distribution and its application to landmark-based localization","display_name":"Robust regression to varying data distribution and its application to landmark-based localization","publication_year":2008,"publication_date":"2008-10-01","ids":{"openalex":"https://openalex.org/W2127013183","doi":"https://doi.org/10.1109/icsmc.2008.4811834","mag":"2127013183"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2008.4811834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2008.4811834","pdf_url":null,"source":{"id":"https://openalex.org/S4210195764","display_name":"Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics","issn_l":"1062-922X","issn":["1062-922X","2577-1655"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Systems, Man and Cybernetics","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/A5017906397","display_name":"Sunglok Choi","orcid":"https://orcid.org/0000-0002-1127-1346"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sunglok Choi","raw_affiliation_strings":["U-Robot Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea","U-Robot Res. Div., Electron. & Telecommun. Res. Inst., Daejeon"],"affiliations":[{"raw_affiliation_string":"U-Robot Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"U-Robot Res. Div., Electron. & Telecommun. Res. Inst., Daejeon","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100718523","display_name":"Jong-Hwan Kim","orcid":"https://orcid.org/0000-0002-4172-4174"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong-Hwan Kim","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, KAIST, Daejeon, South Korea","[Dept. of Electr. Eng. & Comput. Sci., KAIST, Daejeon]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"[Dept. of Electr. Eng. & Comput. Sci., KAIST, Daejeon]","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017906397"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":1.0616,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.73898305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9940000176429749,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9940000176429749,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7732832431793213},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6805882453918457},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.6567431688308716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5848427414894104},{"id":"https://openalex.org/keywords/ransac","display_name":"RANSAC","score":0.49449679255485535},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4688388407230377},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.46175432205200195},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4528712332248688},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4289565086364746},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4270821213722229},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.42261749505996704},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4205038547515869},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4175221920013428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3561837673187256},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3551637530326843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34556883573532104},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33857136964797974},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3035029470920563},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2268144190311432}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7732832431793213},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6805882453918457},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.6567431688308716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5848427414894104},{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.49449679255485535},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4688388407230377},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.46175432205200195},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4528712332248688},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4289565086364746},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4270821213722229},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.42261749505996704},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4205038547515869},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4175221920013428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3561837673187256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3551637530326843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34556883573532104},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33857136964797974},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3035029470920563},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2268144190311432},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2008.4811834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2008.4811834","pdf_url":null,"source":{"id":"https://openalex.org/S4210195764","display_name":"Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics","issn_l":"1062-922X","issn":["1062-922X","2577-1655"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1560964874","https://openalex.org/W1873846702","https://openalex.org/W2026375818","https://openalex.org/W2046434485","https://openalex.org/W2064932843","https://openalex.org/W2085261163","https://openalex.org/W2095905764","https://openalex.org/W2097062302","https://openalex.org/W2102133996","https://openalex.org/W2102901094","https://openalex.org/W2106199912","https://openalex.org/W2116191958","https://openalex.org/W2120933148","https://openalex.org/W2130373531","https://openalex.org/W2135493014","https://openalex.org/W2152701363","https://openalex.org/W2167999499","https://openalex.org/W2322706266","https://openalex.org/W2489822048","https://openalex.org/W4242010931","https://openalex.org/W6639172106","https://openalex.org/W6666416135","https://openalex.org/W6679311991","https://openalex.org/W6700545731"],"related_works":["https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W1976188970","https://openalex.org/W2982058819","https://openalex.org/W2130734797","https://openalex.org/W3176361882","https://openalex.org/W2990541822","https://openalex.org/W2122958477","https://openalex.org/W2025556230","https://openalex.org/W2150061385"],"abstract_inverted_index":{"Data":[0],"may":[1],"be":[2],"wrongly":[3],"measured":[4],"or":[5],"come":[6],"from":[7,21],"other":[8,122,135],"sources.":[9],"Such":[10],"data":[11,49,115],"is":[12,69],"a":[13],"big":[14],"problem":[15],"in":[16,77,113],"regression,":[17],"which":[18,37,68,95],"retrieve":[19],"parameters":[20],"data.":[22,60],"Random":[23],"sample":[24,31],"consensus":[25,32],"(RANSAC)":[26],"and":[27,92,101,111],"maximum":[28],"likelihood":[29],"estimation":[30],"(MLE-SAC)":[33],"are":[34,119],"representative":[35],"researches,":[36],"focused":[38],"on":[39,71],"this":[40],"problem.":[41],"However,":[42],"they":[43,52],"do":[44],"not":[45],"cope":[46],"with":[47,121,134],"varying":[48,114],"distribution":[50],"because":[51],"need":[53],"to":[54,58,126],"tune":[55],"variables":[56,75],"according":[57],"given":[59],"This":[61],"paper":[62],"proposes":[63],"user-independent":[64],"parameter":[65],"estimator,":[66],"u-MLESAC,":[67],"based":[70],"MLESAC.":[72],"It":[73,85],"estimates":[74],"necessary":[76],"probabilistic":[78],"error":[79,93],"model":[80],"through":[81],"expectation":[82],"maximization":[83],"(EM).":[84],"also":[86,129],"terminates":[87],"adaptively":[88],"using":[89],"failure":[90],"rate":[91],"tolerance,":[94],"can":[96],"control":[97],"trade-off":[98],"between":[99],"accuracy":[100,110],"running":[102],"time.":[103],"Line":[104],"fitting":[105],"experiments":[106],"showed":[107],"its":[108,131],"high":[109],"robustness":[112],"distribution.":[116],"Its":[117,124],"results":[118],"compared":[120,133],"estimators.":[123],"application":[125],"landmark-based":[127],"localization":[128],"verified":[130],"performance":[132],"estimator.":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}