{"id":"https://openalex.org/W2787687105","doi":"https://doi.org/10.1109/apsipa.2017.8282121","title":"Stop line detection and distance measurement for road intersection based on deep learning neural network","display_name":"Stop line detection and distance measurement for road intersection based on deep learning neural network","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2787687105","doi":"https://doi.org/10.1109/apsipa.2017.8282121","mag":"2787687105"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2017.8282121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5013459131","display_name":"Guan-Ting Lin","orcid":"https://orcid.org/0000-0001-9895-0060"},"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":true,"raw_author_name":"Guan-Ting Lin","raw_affiliation_strings":["National Chiao Tung University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"National Chiao Tung University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057529712","display_name":"Patrisia Sherryl Santoso","orcid":null},"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":"Patrisia Sherryl Santoso","raw_affiliation_strings":["Industrial Technology Research Institute, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Industrial Technology Research Institute, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I4210148468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102015667","display_name":"Che-Tsung Lin","orcid":"https://orcid.org/0000-0002-5843-7294"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]},{"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":"Che-Tsung Lin","raw_affiliation_strings":["Industrial Technology Research Institute, Hsinchu, Taiwan, R.O.C","National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Industrial Technology Research Institute, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I4210148468"]},{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007783236","display_name":"Chia\u2013Chi Tsai","orcid":"https://orcid.org/0000-0002-2318-6376"},"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":"Chia-Chi Tsai","raw_affiliation_strings":["National Chiao Tung University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"National Chiao Tung University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022312926","display_name":"Jiun-In Guo","orcid":"https://orcid.org/0000-0003-0402-2621"},"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":"Jiun-In Guo","raw_affiliation_strings":["National Chiao Tung University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"National Chiao Tung University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5013459131"],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":0.2731,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66112584,"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":"692","last_page":"695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7804689407348633},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7407868504524231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6964442133903503},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6349275708198547},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.530301570892334},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.49219098687171936},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48936814069747925},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.47051042318344116},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.46239954233169556},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.45066699385643005},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4403862953186035},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43945956230163574},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43911683559417725},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4312880337238312},{"id":"https://openalex.org/keywords/alarm","display_name":"ALARM","score":0.4251352846622467},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.415793240070343},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12107786536216736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08021152019500732},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0791807770729065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7804689407348633},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7407868504524231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6964442133903503},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6349275708198547},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.530301570892334},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.49219098687171936},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48936814069747925},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.47051042318344116},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.46239954233169556},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.45066699385643005},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4403862953186035},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43945956230163574},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43911683559417725},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4312880337238312},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.4251352846622467},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.415793240070343},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12107786536216736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08021152019500732},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0791807770729065},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2017.8282121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W2067866478","https://openalex.org/W2088049833","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2126452053","https://openalex.org/W2145072179","https://openalex.org/W2145073242","https://openalex.org/W2153635508","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2179352600","https://openalex.org/W2206858481","https://openalex.org/W2469962374","https://openalex.org/W2478820856","https://openalex.org/W2963516811","https://openalex.org/W3098722327","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6681554747","https://openalex.org/W6681651645","https://openalex.org/W6684191040","https://openalex.org/W6688059459","https://openalex.org/W6720507930"],"related_works":["https://openalex.org/W1584123598","https://openalex.org/W2731305060","https://openalex.org/W2372003537","https://openalex.org/W1983393909","https://openalex.org/W2040150569","https://openalex.org/W4379535633","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W1911540634","https://openalex.org/W2013909972"],"abstract_inverted_index":{"In":[0,52],"this":[1],"paper,":[2],"we":[3],"introduce":[4],"Boost-CNN,":[5],"a":[6,30,49],"robust":[7],"stop-line":[8,50],"detector":[9,70],"that":[10],"can":[11],"detect":[12],"objects":[13],"(stop":[14],"line)":[15],"with":[16,44],"competitive":[17],"tradeoff":[18],"between":[19],"speed":[20],"and":[21,29,39,75,88],"accuracy.":[22],"Boost-CNN":[23],"consists":[24],"of":[25,65],"an":[26,54],"AdaBoost":[27],"classifier":[28],"CNN.":[31],"The":[32],"former":[33],"is":[34,41,59],"our":[35],"region":[36],"proposal":[37],"generator":[38],"it":[40],"further":[42],"combined":[43],"the":[45,63],"later":[46],"to":[47,61],"be":[48],"detector.":[51],"addition,":[53],"automatic":[55],"hard":[56],"mining":[57],"method":[58],"proposed":[60,69],"reduce":[62],"number":[64],"false":[66],"alarm.":[67],"Our":[68],"achieves":[71],"91.5%":[72],"in":[73,80],"accuracy":[74],"has":[76],"100":[77],"FPS":[78],"performance":[79],"test":[81],"time":[82],"(performed":[83],"on":[84],"NVIDIA":[85],"DIGITS":[86],"DevBox":[87],"Titan":[89],"X":[90],"GPU).":[91]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}