{"id":"https://openalex.org/W3007797751","doi":"https://doi.org/10.1109/ssci44817.2019.9003046","title":"CNN-based Super-resolution Reconstruction for Traffic Sign Detection","display_name":"CNN-based Super-resolution Reconstruction for Traffic Sign Detection","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007797751","doi":"https://doi.org/10.1109/ssci44817.2019.9003046","mag":"3007797751"},"language":"en","primary_location":{"id":"doi:10.1109/ssci44817.2019.9003046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9003046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5100719173","display_name":"Fan Wang","orcid":"https://orcid.org/0000-0001-7320-1119"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fan Wang","raw_affiliation_strings":["Fuzhou university,College of Electrical Engineering and Automation,Fujian,China,350116"],"affiliations":[{"raw_affiliation_string":"Fuzhou university,College of Electrical Engineering and Automation,Fujian,China,350116","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100699193","display_name":"Jianqi Shi","orcid":"https://orcid.org/0000-0002-8993-7603"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqi Shi","raw_affiliation_strings":["East China Normal University,Shanghai Key Lab for Trustworthy Computing School of Software Engineering,Shanghai,Putuo District","Shanghai Key Lab for Trustworthy Computing School of Software Engineering, East China Normal University, Shanghai, Putuo District"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Lab for Trustworthy Computing School of Software Engineering,Shanghai,Putuo District","institution_ids":["https://openalex.org/I4210139618"]},{"raw_affiliation_string":"Shanghai Key Lab for Trustworthy Computing School of Software Engineering, East China Normal University, Shanghai, Putuo District","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101602073","display_name":"Xuan Tang","orcid":"https://orcid.org/0000-0002-2041-5268"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210151023","display_name":"Quanzhou Institute of Equipment Manufacturing Haixi Institute","ror":"https://ror.org/05ev3vr27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Tang","raw_affiliation_strings":["Haixi Institutes, Chinese Academy of Sciences,Quanzhou Institute of Equipment Manufacture,Quanzhou,China","Quanzhou Institute of Equipment Manufacture, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China"],"affiliations":[{"raw_affiliation_string":"Haixi Institutes, Chinese Academy of Sciences,Quanzhou Institute of Equipment Manufacture,Quanzhou,China","institution_ids":["https://openalex.org/I4210151023"]},{"raw_affiliation_string":"Quanzhou Institute of Equipment Manufacture, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China","institution_ids":["https://openalex.org/I4210151023","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023434920","display_name":"Jielong Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210151023","display_name":"Quanzhou Institute of Equipment Manufacturing Haixi Institute","ror":"https://ror.org/05ev3vr27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jielong Guo","raw_affiliation_strings":["Haixi Institutes, Chinese Academy of Sciences,Quanzhou Institute of Equipment Manufacture,Quanzhou,China","Quanzhou Institute of Equipment Manufacture, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China"],"affiliations":[{"raw_affiliation_string":"Haixi Institutes, Chinese Academy of Sciences,Quanzhou Institute of Equipment Manufacture,Quanzhou,China","institution_ids":["https://openalex.org/I4210151023"]},{"raw_affiliation_string":"Quanzhou Institute of Equipment Manufacture, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China","institution_ids":["https://openalex.org/I4210151023","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109423323","display_name":"Peidong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I169019527","display_name":"Quanzhou Normal University","ror":"https://ror.org/006ak0b38","country_code":"CN","type":"education","lineage":["https://openalex.org/I169019527"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peidong Liang","raw_affiliation_strings":["Quanzhou HIT Research Institute of Engineering and Technology,Quanzhou,Fengze District,China","Quanzhou HIT Research Institute of Engineering and Technology, Quanzhou, Fengze District, China"],"affiliations":[{"raw_affiliation_string":"Quanzhou HIT Research Institute of Engineering and Technology,Quanzhou,Fengze District,China","institution_ids":["https://openalex.org/I169019527"]},{"raw_affiliation_string":"Quanzhou HIT Research Institute of Engineering and Technology, Quanzhou, Fengze District, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027381668","display_name":"Yuanzhi Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]},{"id":"https://openalex.org/I4210100137","display_name":"Kaifeng University","ror":"https://ror.org/012nfwd22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210100137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanzhi Feng","raw_affiliation_strings":["Henan University North Section of Jinming Avenue,Kaifeng,Longting District,China","Henan University North Section of Jinming Avenue, Kaifeng, Longting District, China"],"affiliations":[{"raw_affiliation_string":"Henan University North Section of Jinming Avenue,Kaifeng,Longting District,China","institution_ids":["https://openalex.org/I173899330","https://openalex.org/I4210100137"]},{"raw_affiliation_string":"Henan University North Section of Jinming Avenue, Kaifeng, Longting District, China","institution_ids":["https://openalex.org/I173899330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100719173"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18340681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1208","last_page":"1213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.996999979019165,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.996999979019165,"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":0.9945999979972839,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9887999892234802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8086676001548767},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.7770410776138306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6983298659324646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6470195055007935},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.571792721748352},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5468562841415405},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.5187357068061829},{"id":"https://openalex.org/keywords/low-resolution","display_name":"Low resolution","score":0.49128907918930054},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4808581471443176},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.45200106501579285},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4449802041053772},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44439804553985596},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4300433397293091},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4138898253440857},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.3399885594844818},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32621800899505615},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.07512795925140381}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8086676001548767},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.7770410776138306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6983298659324646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6470195055007935},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.571792721748352},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5468562841415405},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.5187357068061829},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.49128907918930054},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4808581471443176},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.45200106501579285},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4449802041053772},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44439804553985596},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4300433397293091},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4138898253440857},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.3399885594844818},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32621800899505615},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.07512795925140381},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci44817.2019.9003046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9003046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1576520375","https://openalex.org/W2099471712","https://openalex.org/W2102605133","https://openalex.org/W2117876524","https://openalex.org/W2120419212","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2284050935","https://openalex.org/W2428809231","https://openalex.org/W2476548250","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2769986739","https://openalex.org/W2796347433","https://openalex.org/W2888285221","https://openalex.org/W2952393781","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963685250","https://openalex.org/W3023553797","https://openalex.org/W3106250896","https://openalex.org/W3122330358","https://openalex.org/W4293584584","https://openalex.org/W4320013936","https://openalex.org/W6620707391","https://openalex.org/W6634442568","https://openalex.org/W6675026286","https://openalex.org/W6684191040","https://openalex.org/W6695676441","https://openalex.org/W6750227808","https://openalex.org/W6754089586","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4283820116","https://openalex.org/W4379231512","https://openalex.org/W4378699879","https://openalex.org/W3128164723","https://openalex.org/W4286647459","https://openalex.org/W2899819381","https://openalex.org/W2557202782","https://openalex.org/W3215426395","https://openalex.org/W4382176313"],"abstract_inverted_index":{"Automatic":[0],"identification":[1],"for":[2,48,62,100,117,143],"traffic":[3,13,24,49,68,121,144],"signs":[4],"is":[5,74],"an":[6],"important":[7],"part":[8],"of":[9,67,89],"intelligent":[10],"driving":[11],"and":[12,38,120],"safety.":[14],"Deep":[15],"learning":[16],"has":[17],"already":[18],"made":[19],"a":[20,31,35,55,71,81],"great":[21],"achievement":[22],"in":[23,41,107],"sign":[25,50,122,145],"detection.":[26,51,146],"However,":[27],"the":[28,64,87,94,101,126,140],"camera":[29],"on":[30,58],"car":[32],"may":[33],"capture":[34],"low":[36],"resolution":[37],"blurry":[39],"image":[40,59,73,97],"certain":[42],"environments,":[43],"which":[44,124],"make":[45],"it":[46],"inaccurate":[47],"Therefore,":[52],"we":[53,92,112],"propose":[54],"method":[56],"based":[57],"super-resolution":[60,78,96,118],"reconstruction":[61,119],"improving":[63],"detection":[65,102],"rate":[66],"signs.":[69],"Firstly,":[70],"low-resolution":[72],"transformed":[75],"by":[76],"CNN-based":[77],"network":[79,103],"into":[80],"high-resolution":[82],"one.":[83],"Then,":[84],"to":[85],"meet":[86],"requirements":[88],"on-line":[90],"processing,":[91],"use":[93],"generated":[95],"as":[98],"input":[99],"with":[104],"16":[105],"filters":[106],"this":[108],"layer.":[109],"At":[110],"last,":[111],"separately":[113],"trained":[114],"two":[115],"CNNs":[116],"detection,":[123],"reduce":[125],"processing":[127],"time.":[128],"Experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"our":[133],"model":[134],"can":[135],"achieve":[136],"better":[137],"performance":[138],"than":[139],"existing":[141],"methods":[142]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}