{"id":"https://openalex.org/W3094541847","doi":"https://doi.org/10.1109/icpr48806.2021.9412572","title":"RONELD: Robust Neural Network Output Enhancement for Active Lane Detection","display_name":"RONELD: Robust Neural Network Output Enhancement for Active Lane Detection","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3094541847","doi":"https://doi.org/10.1109/icpr48806.2021.9412572","mag":"3094541847"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412572","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":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.09548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017553257","display_name":"Zhe Ming Chng","orcid":"https://orcid.org/0000-0002-4704-0718"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Ming Chng","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA","#N#\u2021#N#Georgia Institute of Technology#N#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"#N#\u2021#N#Georgia Institute of Technology#N#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082117788","display_name":"Joseph Mun Hung Lew","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joseph Mun Hung Lew","raw_affiliation_strings":["Aviation A.I. Lab Pte. Ltd., Singapore, Singapore","Aviation A.I. Lab Pte. Ltd.,Singapore,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aviation A.I. Lab Pte. Ltd., Singapore, Singapore","institution_ids":[]},{"raw_affiliation_string":"Aviation A.I. Lab Pte. Ltd.,Singapore,Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068292501","display_name":"Jimmy Addison Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jimmy Addison Lee","raw_affiliation_strings":["Aviation A.I. Lab Pte. Ltd., Singapore, Singapore","Aviation A.I. Lab Pte. Ltd.,Singapore,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aviation A.I. Lab Pte. Ltd., Singapore, Singapore","institution_ids":[]},{"raw_affiliation_string":"Aviation A.I. Lab Pte. Ltd.,Singapore,Singapore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.093,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36972839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"6842","last_page":"6849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9970999956130981,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901999831199646,"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/computer-science","display_name":"Computer science","score":0.7069423794746399},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6840657591819763},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.637939453125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4966638684272766},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4620506167411804},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4469432830810547},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4356898069381714},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4206628203392029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7069423794746399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6840657591819763},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.637939453125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4966638684272766},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4620506167411804},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4469432830810547},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4356898069381714},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4206628203392029},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412572","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:arXiv.org:2010.09548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.09548","pdf_url":"https://arxiv.org/pdf/2010.09548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"mag:3094541847","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.09548","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2010.09548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.09548","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.09548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.09548","pdf_url":"https://arxiv.org/pdf/2010.09548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3094541847.pdf","grobid_xml":"https://content.openalex.org/works/W3094541847.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1809628376","https://openalex.org/W1829670322","https://openalex.org/W1995700534","https://openalex.org/W2006244290","https://openalex.org/W2039544046","https://openalex.org/W2049182791","https://openalex.org/W2065014583","https://openalex.org/W2080553371","https://openalex.org/W2082747607","https://openalex.org/W2094263170","https://openalex.org/W2103866601","https://openalex.org/W2106976646","https://openalex.org/W2118545852","https://openalex.org/W2133648827","https://openalex.org/W2151362034","https://openalex.org/W2156128637","https://openalex.org/W2194775991","https://openalex.org/W2211466563","https://openalex.org/W2245493112","https://openalex.org/W2291533584","https://openalex.org/W2419448466","https://openalex.org/W2478820856","https://openalex.org/W2914238185","https://openalex.org/W2963611454","https://openalex.org/W2963856865","https://openalex.org/W2964199920","https://openalex.org/W2964332990","https://openalex.org/W2981441441","https://openalex.org/W2981992989","https://openalex.org/W2989279786","https://openalex.org/W3003398009","https://openalex.org/W3006566272","https://openalex.org/W3034879391","https://openalex.org/W3100397002","https://openalex.org/W3102168793","https://openalex.org/W6675534850","https://openalex.org/W6717372056","https://openalex.org/W6747394537","https://openalex.org/W6752610181","https://openalex.org/W6773691707"],"related_works":["https://openalex.org/W3162064550","https://openalex.org/W2909530718","https://openalex.org/W3041442181","https://openalex.org/W3084439521","https://openalex.org/W2922121771","https://openalex.org/W2791043287","https://openalex.org/W3208338121","https://openalex.org/W2946949691","https://openalex.org/W3007653929","https://openalex.org/W3010603606","https://openalex.org/W2956540074","https://openalex.org/W3023336500","https://openalex.org/W2780742574","https://openalex.org/W2913045229","https://openalex.org/W2980449628","https://openalex.org/W2971079005","https://openalex.org/W2804070054","https://openalex.org/W3002702040","https://openalex.org/W2296223440","https://openalex.org/W2908825945"],"abstract_inverted_index":{"Accurate":[0],"lane":[1,13,29,92,113,140],"detection":[2,30,93],"is":[3,23],"critical":[4],"for":[5,90],"navigation":[6],"in":[7,148,169],"autonomous":[8],"vehicles,":[9],"particularly":[10,56],"the":[11,16,21,65,68,116],"active":[12,91,101,155],"which":[14],"demarcates":[15],"single":[17],"road":[18],"space":[19],"that":[20],"vehicle":[22],"currently":[24],"traveling":[25],"on.":[26],"Recent":[27],"state-of-the-art":[28],"algorithms":[31],"utilize":[32],"convolutional":[33],"neural":[34,86],"networks":[35],"(CNNs)":[36],"to":[37,96,137,166],"train":[38,59],"deep":[39,104],"learning":[40,105],"models":[41,54],"on":[42,58,72,134,173],"popular":[43],"benchmarks":[44],"such":[45],"as":[46],"TuSimple":[47],"and":[48,60,99,124],"CULane.":[49],"While":[50],"each":[51],"of":[52,75,145],"these":[53],"works":[55],"well":[57],"test":[61],"inputs":[62],"obtained":[63],"from":[64,103,115,143],"same":[66],"dataset,":[67],"performance":[69],"drops":[70],"significantly":[71],"unseen":[73],"datasets":[74],"different":[76],"environments.":[77],"In":[78],"this":[79],"paper,":[80],"we":[81,152],"present":[82],"a":[83],"real-time":[84],"robust":[85],"network":[87],"output":[88],"enhancement":[89],"(RONELD)":[94],"method":[95],"identify,":[97],"track,":[98],"optimize":[100],"lanes":[102,126,136,156],"probability":[106,117],"map":[107,118],"outputs.":[108],"We":[109],"first":[110],"adaptively":[111],"extract":[112],"points":[114],"outputs,":[119],"followed":[120],"by":[121],"detecting":[122],"curved":[123],"straight":[125,135],"before":[127],"using":[128,171],"weighted":[129],"least":[130],"squares":[131],"linear":[132],"regression":[133],"fix":[138],"broken":[139],"edges":[141],"resulting":[142],"fragmentation":[144],"edge":[146],"maps":[147],"real":[149],"images.":[150],"Lastly,":[151],"hypothesize":[153],"true":[154],"through":[157],"tracking":[158],"preceding":[159],"frames.":[160],"Experimental":[161],"results":[162],"demonstrate":[163],"an":[164],"up":[165],"two-fold":[167],"increase":[168],"accuracy":[170],"RONELD":[172],"cross-dataset":[174],"validation":[175],"tests.":[176]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}