{"id":"https://openalex.org/W2962830262","doi":"https://doi.org/10.1109/icdsp.2018.8631673","title":"Efficient Road Lane Marking Detection with Deep Learning","display_name":"Efficient Road Lane Marking Detection with Deep Learning","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2962830262","doi":"https://doi.org/10.1109/icdsp.2018.8631673","mag":"2962830262"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2018.8631673","doi":"https://doi.org/10.1109/icdsp.2018.8631673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631673","pdf_url":null,"source":{"id":"https://openalex.org/S7407086640","display_name":"IEEE International Conference on Digital Signal Processing (DSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.03994","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065794766","display_name":"Ping-Rong Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ping-Rong Chen","raw_affiliation_strings":["Electronics Institute, ECE College, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Institute, ECE College, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073032555","display_name":"Shao-Yuan Lo","orcid":"https://orcid.org/0000-0002-9506-794X","observed_orcids":["https://orcid.org/0000-0002-9506-794X"]},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shao-Yuan Lo","raw_affiliation_strings":["Electronics Institute, ECE College, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Institute, ECE College, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033363752","display_name":"Hsueh\u2010Ming Hang","orcid":"https://orcid.org/0000-0001-8965-2619","observed_orcids":["https://orcid.org/0000-0001-8965-2619"]},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsueh-Ming Hang","raw_affiliation_strings":["Electronics Institute, ECE College, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Institute, ECE College, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003841135","display_name":"Sheng-Wei Chan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148468","display_name":"Industrial Technology Research Institute","ror":"https://ror.org/05szzwt63","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I4210148468"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sheng-Wei Chan","raw_affiliation_strings":["Mechanical and Mechatronics Systems Research Lab, Industrial Tech Research Inst, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical and Mechatronics Systems Research Lab, Industrial Tech Research Inst, Taiwan","institution_ids":["https://openalex.org/I4210148468"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000679043","display_name":"Jing-Jhih Lin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148468","display_name":"Industrial Technology Research Institute","ror":"https://ror.org/05szzwt63","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I4210148468"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jing-Jhih Lin","raw_affiliation_strings":["Mechanical and Mechatronics Systems Research Lab, Industrial Tech Research Inst, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical and Mechatronics Systems Research Lab, Industrial Tech Research Inst, Taiwan","institution_ids":["https://openalex.org/I4210148468"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.2347,"has_fulltext":true,"cited_by_count":78,"citation_normalized_percentile":{"value":0.98960074,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9897000193595886,"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":0.9897000193595886,"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":0.00989999994635582,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":9.999999747378752e-05,"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/lane-detection","display_name":"lane detection","score":0.9300000071525574},{"id":"https://openalex.org/keywords/road-scene-analysis","display_name":"road scene analysis","score":0.7620000243186951},{"id":"https://openalex.org/keywords/driver-assistance-systems","display_name":"driver assistance systems","score":0.9380000233650208},{"id":"https://openalex.org/keywords/dilated-convolution","display_name":"dilated convolution","score":0.9210000038146973},{"id":"https://openalex.org/keywords/lightweight-convolutional-neural-network","display_name":"lightweight convolutional neural network","score":0.7829999923706055},{"id":"https://openalex.org/keywords/polynomial-fitting","display_name":"polynomial fitting","score":0.5450000166893005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7227711081504822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6458221673965454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6439843773841858},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6234442591667175},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5437565445899963},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5168529152870178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5111027359962463},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.50832599401474},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4711436331272125},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.4575175344944},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.45645472407341003},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4315112233161926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34912240505218506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3395538330078125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26481783390045166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11624425649642944},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icdsp.2018.8631673","doi":"https://doi.org/10.1109/icdsp.2018.8631673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631673","pdf_url":null,"source":{"id":"https://openalex.org/S7407086640","display_name":"IEEE International Conference on Digital Signal Processing (DSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1809.03994","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.03994","pdf_url":"https://arxiv.org/pdf/1809.03994","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"doi:10.48550/arxiv.1809.03994","doi":"https://doi.org/10.48550/arxiv.1809.03994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1809.03994","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.03994","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.03994","pdf_url":"https://arxiv.org/pdf/1809.03994","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":0.651199996471405,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962830262.pdf","grobid_xml":"https://content.openalex.org/works/W2962830262.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1910657905","https://openalex.org/W2038270407","https://openalex.org/W2041310334","https://openalex.org/W2042105889","https://openalex.org/W2103866601","https://openalex.org/W2117539524","https://openalex.org/W2150066425","https://openalex.org/W2155893237","https://openalex.org/W2171943915","https://openalex.org/W2194775991","https://openalex.org/W2286929393","https://openalex.org/W2412782625","https://openalex.org/W2419448466","https://openalex.org/W2431874326","https://openalex.org/W2607662938","https://openalex.org/W2949117887"],"related_works":["https://openalex.org/W3194221360","https://openalex.org/W3128544682","https://openalex.org/W3117142677","https://openalex.org/W4281392050","https://openalex.org/W3086153693","https://openalex.org/W4293064092","https://openalex.org/W4304172553","https://openalex.org/W3015811284","https://openalex.org/W2790755431","https://openalex.org/W4322761354"],"abstract_inverted_index":{"Lane":[0,47],"mark":[1],"detection":[2],"is":[3,25,75,82],"an":[4],"important":[5],"element":[6],"in":[7],"the":[8,20,38,72,86,103,112],"road":[9,114],"scene":[10],"analysis":[11],"for":[12],"Advanced":[13],"Driver":[14],"Assistant":[15],"System":[16],"(ADAS).":[17],"Limited":[18],"by":[19],"onboard":[21],"computing":[22],"power,":[23],"it":[24],"still":[26],"a":[27,46,67],"challenge":[28],"to":[29,56,84,95,100],"reduce":[30],"system":[31,107],"complexity":[32],"and":[33,79],"maintain":[34],"high":[35],"accuracy":[36],"at":[37],"same":[39],"time.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44,90],"propose":[45],"Marking":[48],"Detector":[49],"(LMD)":[50],"using":[51],"deep":[52],"convolutional":[53],"neural":[54],"network":[55],"extract":[57],"robust":[58],"lane":[59],"marking":[60],"features.":[61],"To":[62],"improve":[63],"its":[64],"performance":[65],"with":[66],"target":[68],"of":[69],"lower":[70],"complexity,":[71],"dilated":[73],"convolution":[74],"adopted.":[76],"A":[77],"shallower":[78],"thinner":[80],"structure":[81],"designed":[83],"decrease":[85],"computational":[87],"cost.":[88],"Moreover,":[89],"also":[91],"design":[92],"post-processing":[93],"algorithms":[94],"construct":[96],"3rd-oder":[97],"polynomial":[98],"models":[99],"fit":[101],"into":[102],"curved":[104],"lanes.":[105],"Our":[106],"shows":[108],"promising":[109],"results":[110],"on":[111],"captured":[113],"scenes.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":6}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-07-30T00:00:00"}