{"id":"https://openalex.org/W2088600512","doi":"https://doi.org/10.1109/tits.2013.2287155","title":"Rail Component Detection, Optimization, and Assessment for Automatic Rail Track Inspection","display_name":"Rail Component Detection, Optimization, and Assessment for Automatic Rail Track Inspection","publication_year":2013,"publication_date":"2013-11-19","ids":{"openalex":"https://openalex.org/W2088600512","doi":"https://doi.org/10.1109/tits.2013.2287155","mag":"2088600512"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2013.2287155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2013.2287155","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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/A5086689347","display_name":"Ying Li","orcid":"https://orcid.org/0000-0001-5887-3937"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000099875","display_name":"Hoang Duy Trinh","orcid":"https://orcid.org/0000-0001-5511-6957"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]},{"id":"https://openalex.org/I4210139270","display_name":"UtopiaCompression (United States)","ror":"https://ror.org/051d4q284","country_code":"US","type":"company","lineage":["https://openalex.org/I4210139270"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hoang Trinh","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, UtopiaCompression, Los Angeles, CA, USA","[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, UtopiaCompression, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4210114115","https://openalex.org/I4210139270"]},{"raw_affiliation_string":"[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039564215","display_name":"Norman Haas","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Norman Haas","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051110127","display_name":"Charles Otto","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]},{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles Otto","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Michigan State University, East Lansing, MI, USA","[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I4210114115","https://openalex.org/I87216513"]},{"raw_affiliation_string":"[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078542580","display_name":"Sharath Pankanti","orcid":"https://orcid.org/0000-0001-6770-9899"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharath Pankanti","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"[IBM Thomas J. Watson Research Center, Yorktown Heights, NY , USA]","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.3667,"has_fulltext":false,"cited_by_count":158,"citation_normalized_percentile":{"value":0.97875225,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"15","issue":"2","first_page":"760","last_page":"770"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/false-positive-paradox","display_name":"False positive paradox","score":0.6334336996078491},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5775575041770935},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.5378552675247192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5194213390350342},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5110993981361389},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.482854425907135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46778571605682373},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46424993872642517},{"id":"https://openalex.org/keywords/fastener","display_name":"Fastener","score":0.4499087929725647},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4399334490299225},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4373451769351959},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32228392362594604}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6334336996078491},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5775575041770935},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.5378552675247192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5194213390350342},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5110993981361389},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.482854425907135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46778571605682373},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46424993872642517},{"id":"https://openalex.org/C2778240408","wikidata":"https://www.wikidata.org/wiki/Q2002016","display_name":"Fastener","level":2,"score":0.4499087929725647},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4399334490299225},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4373451769351959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32228392362594604},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2013.2287155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2013.2287155","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1503535157","https://openalex.org/W2025613153","https://openalex.org/W2040883920","https://openalex.org/W2109799377","https://openalex.org/W2126893197","https://openalex.org/W2142037471","https://openalex.org/W2146352414","https://openalex.org/W2164598857","https://openalex.org/W2293962155","https://openalex.org/W2527427430","https://openalex.org/W2539604081","https://openalex.org/W4241222664","https://openalex.org/W6727574183"],"related_works":["https://openalex.org/W2381731832","https://openalex.org/W2020631818","https://openalex.org/W2910075253","https://openalex.org/W2889060475","https://openalex.org/W1970316032","https://openalex.org/W4205192237","https://openalex.org/W293705464","https://openalex.org/W4226078381","https://openalex.org/W2064707553","https://openalex.org/W1955599488"],"abstract_inverted_index":{"In":[0],"this":[1,46,219],"paper,":[2],"we":[3,48,96],"present":[4],"a":[5,19,51,61,129,145,183],"real-time":[6,146],"automatic":[7],"vision-based":[8],"rail":[9,30,94,156,180,220],"inspection":[10,221],"system,":[11],"which":[12,106],"performs":[13],"inspections":[14],"at":[15,112,121],"16":[16],"km/h":[17],"with":[18,39,135,193],"frame":[20],"rate":[21,172,186],"of":[22,53,93,166],"20":[23],"fps.":[24],"The":[25],"system":[26,204],"robustly":[27],"detects":[28],"important":[29,91],"components":[31],"such":[32],"as":[33,86,141,143],"ties,":[34],"tie":[35,114],"plates,":[36],"and":[37,42,55,58,75,116,138,159,169,182,210,214],"anchors,":[38],"high":[40],"accuracy":[41],"efficiency.":[43],"To":[44,199],"achieve":[45],"goal,":[47],"first":[49,207],"develop":[50],"set":[52,133],"image":[54],"video":[56,131],"analytics":[57],"then":[59],"propose":[60],"novel":[62],"global":[63],"optimization":[64],"framework":[65],"to":[66,79,102,208],"combine":[67],"evidence":[68],"from":[69],"multiple":[70],"cameras,":[71],"Global":[72],"Positioning":[73],"System,":[74],"distance":[76],"measurement":[77],"instrument":[78],"further":[80],"improve":[81],"the":[82,87,100,109,113,122,206],"detection":[83,158,185,216],"performance.":[84],"Moreover,":[85],"anchor":[88,104,110,118,160,191],"is":[89,187,205],"an":[90,164],"type":[92],"fastener,":[95],"have":[97],"thus":[98],"advanced":[99],"effort":[101],"detect":[103],"exceptions,":[105],"includes":[107],"assessing":[108],"conditions":[111],"level":[115],"identifying":[117],"pattern":[119],"exceptions":[120],"compliance":[123],"level.":[124],"Quantitative":[125],"analysis":[126],"performed":[127],"on":[128,144,154],"large":[130],"data":[132],"captured":[134],"different":[136],"track":[137],"lighting":[139],"conditions,":[140],"well":[142],"field":[147],"test,":[148],"has":[149,173],"demonstrated":[150],"very":[151],"encouraging":[152],"performance":[153],"both":[155,212],"component":[157,213],"exception":[161,192,215],"detection.":[162],"Specifically,":[163],"average":[165],"94.67%":[167],"precision":[168],"93%":[170],"recall":[171],"been":[174],"achieved":[175,188],"for":[176,189],"detecting":[177],"all":[178],"three":[179,194],"components,":[181],"100%":[184],"compliance-level":[190],"false":[195],"positives":[196],"per":[197],"hour.":[198],"our":[200,203],"best":[201],"knowledge,":[202],"address":[209],"solve":[211],"problems":[217],"in":[218],"area.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":8}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
