{"id":"https://openalex.org/W1970730235","doi":"https://doi.org/10.1109/itsc.2013.6728530","title":"Turnout detection and classification using a modified HOG and template matching","display_name":"Turnout detection and classification using a modified HOG and template matching","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W1970730235","doi":"https://doi.org/10.1109/itsc.2013.6728530","mag":"1970730235"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2013.6728530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2013.6728530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","raw_type":"proceedings-article"},"type":"preprint","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/A5011855936","display_name":"Jorge Corsino Espino","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jorge Corsino Espino","raw_affiliation_strings":["Mathematics and Computer Vision Science, SIEMENS S.A.S. Infrastructure & Cities, Division Mobility and Logistics, 92320 Chatillon, France","Div. Mobility & Logistics, SIEMENS S.A.S. Infrastruct. & Cities, Chatillon, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematics and Computer Vision Science, SIEMENS S.A.S. Infrastructure & Cities, Division Mobility and Logistics, 92320 Chatillon, France","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"Div. Mobility & Logistics, SIEMENS S.A.S. Infrastruct. & Cities, Chatillon, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071519130","display_name":"Bogdan Stanciulescu","orcid":null},"institutions":[{"id":"https://openalex.org/I70768539","display_name":"\u00c9cole Nationale Sup\u00e9rieure des Mines de Paris","ror":"https://ror.org/04y8cs423","country_code":"FR","type":"education","lineage":["https://openalex.org/I190752583","https://openalex.org/I2746051580","https://openalex.org/I70768539"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Bogdan Stanciulescu","raw_affiliation_strings":["Robotics center, Paris, France","Robot. Center, MINES ParisTech, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics center, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Robot. Center, MINES ParisTech, Paris, France","institution_ids":["https://openalex.org/I70768539"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2441,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.79820727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2045","last_page":"2050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9961000084877014,"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"}},"topics":[{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9961000084877014,"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"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9958000183105469,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/turnout","display_name":"Turnout","score":0.9403371810913086},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7420703172683716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6386513113975525},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6183258891105652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5971692800521851},{"id":"https://openalex.org/keywords/classification-scheme","display_name":"Classification scheme","score":0.4717871844768524},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46268430352211},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4410635232925415},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.43531256914138794},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4264979362487793},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33241599798202515},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2019173800945282},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1294759213924408},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1284540295600891},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.11616784334182739}],"concepts":[{"id":"https://openalex.org/C2779838221","wikidata":"https://www.wikidata.org/wiki/Q7856080","display_name":"Turnout","level":4,"score":0.9403371810913086},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7420703172683716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6386513113975525},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6183258891105652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5971692800521851},{"id":"https://openalex.org/C13460635","wikidata":"https://www.wikidata.org/wiki/Q85753676","display_name":"Classification scheme","level":2,"score":0.4717871844768524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46268430352211},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4410635232925415},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.43531256914138794},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4264979362487793},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33241599798202515},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2019173800945282},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1294759213924408},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1284540295600891},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.11616784334182739},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2013.6728530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2013.6728530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01517892v1","is_oa":false,"landing_page_url":"https://minesparis-psl.hal.science/hal-01517892","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ieeexplore.ieee.org/document/6728530/","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1974074792","https://openalex.org/W2054566720","https://openalex.org/W2085261163","https://openalex.org/W2122679244","https://openalex.org/W2131076267","https://openalex.org/W2161969291","https://openalex.org/W2164323537","https://openalex.org/W2172000360","https://openalex.org/W2491179239"],"related_works":["https://openalex.org/W2044173263","https://openalex.org/W856308142","https://openalex.org/W2373209389","https://openalex.org/W2197796436","https://openalex.org/W2264221613","https://openalex.org/W4246879814","https://openalex.org/W2110286895","https://openalex.org/W1168036533","https://openalex.org/W2168661258","https://openalex.org/W2050081829"],"abstract_inverted_index":{"This":[0,30],"paper":[1],"presents":[2],"a":[3,92,104],"railway":[4,14,87],"track":[5,15,88],"and":[6,9,67],"turnout":[7,10,55,72,100,111],"detection":[8,22,32,56,79,101],"classification":[11,73,112],"algorithm.":[12],"The":[13,54,71,78,110],"extraction":[16,89],"is":[17,34,58,74],"based":[18,59,75],"on":[19,60,76],"an":[20,38],"edge":[21,31],"using":[23,103,119],"the":[24,27,41,46,49,61,99],"width":[25],"of":[26,48,63,95,116],"rolling":[28],"pads.":[29],"scheme":[33,57,102],"then":[35],"used":[36],"as":[37],"input":[39],"to":[40,44],"RANSAC":[42],"algorithm":[43],"determine":[45],"model":[47],"rails":[50],"knowing":[51],"their":[52],"gauge.":[53],"Histogram":[62],"Oriented":[64],"Gradient":[65],"(HOG)":[66],"Template":[68],"Matching":[69],"(TM).":[70],"HOG.":[77],"results":[80],"show":[81],"(i)":[82],"reliable":[83],"performance":[84],"for":[85,98],"our":[86],"scheme;":[90],"(ii)":[91],"correction":[93,114],"rate":[94,115],"97.31":[96],"percent":[97,118],"Support":[105],"Vector":[106],"Machine":[107],"(SVM)":[108],"classifier.":[109],"has":[113],"98.72":[117],"SVM.":[120]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
