{"id":"https://openalex.org/W3013808268","doi":"https://doi.org/10.1145/3383812.3383819","title":"Street Sign Recognition Algorithm Based on Deep Learning","display_name":"Street Sign Recognition Algorithm Based on Deep Learning","publication_year":2020,"publication_date":"2020-02-08","ids":{"openalex":"https://openalex.org/W3013808268","doi":"https://doi.org/10.1145/3383812.3383819","mag":"3013808268"},"language":"en","primary_location":{"id":"doi:10.1145/3383812.3383819","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383812.3383819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Image and Graphics Processing","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/A5100388745","display_name":"Jiawei Wang","orcid":"https://orcid.org/0000-0001-5037-4658"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622590","display_name":"Cen Chen","orcid":"https://orcid.org/0000-0003-1389-0148"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cen Chen","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101941815","display_name":"Chongwen Wang","orcid":"https://orcid.org/0000-0003-0203-3167"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongwen Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0979,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.37177938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9997000098228455,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9997000098228455,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9962999820709229,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.680392861366272},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.6485809087753296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5692391395568848},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.555432140827179},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43434250354766846},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42868179082870483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4146222174167633},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3208709955215454},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14792516827583313}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.680392861366272},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.6485809087753296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5692391395568848},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.555432140827179},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43434250354766846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42868179082870483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4146222174167633},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3208709955215454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14792516827583313},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383812.3383819","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383812.3383819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W2194187530","https://openalex.org/W2343052201","https://openalex.org/W2606394513","https://openalex.org/W2613718673","https://openalex.org/W2772895882","https://openalex.org/W2788097838","https://openalex.org/W2817549221","https://openalex.org/W2892078387","https://openalex.org/W6736305252"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2110143569","https://openalex.org/W3122938442","https://openalex.org/W2611989081","https://openalex.org/W2025206082","https://openalex.org/W2164424388","https://openalex.org/W2522576680","https://openalex.org/W2136335912","https://openalex.org/W2039574433","https://openalex.org/W2330714393"],"abstract_inverted_index":{"The":[0],"complex":[1],"background,":[2],"uneven":[3],"illumination":[4],"and":[5,27,59],"object":[6,23],"occlusion":[7],"have":[8],"increased":[9],"the":[10,21,48,64,74,78,84,93,96],"difficulty":[11],"of":[12,55],"scene":[13],"texts":[14],"detection.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19,67],"improved":[20],"existing":[22],"detection":[24,75,97],"algorithm":[25,76],"SSD,":[26],"made":[28],"it":[29],"possible":[30],"to":[31,46,72,92],"detect":[32],"text":[33,79],"objects":[34],"in":[35],"traffic":[36],"guidance":[37],"sign.":[38],"We":[39],"used":[40],"a":[41,53,69,109],"deep":[42],"neural":[43],"network":[44,51,86,98],"CRNN":[45],"identify":[47],"text.":[49],"This":[50],"is":[52],"combination":[54],"Convolution":[56],"Neural":[57,61],"Network":[58],"Recurrent":[60],"Network.":[62],"At":[63],"same":[65],"time,":[66],"proposed":[68],"new":[70],"idea":[71],"optimize":[73],"through":[77],"recognition":[80,111],"result,":[81],"so":[82],"that":[83],"whole":[85],"can":[87],"be":[88],"trained":[89],"end-to-end.":[90],"According":[91],"experimental":[94],"results,":[95],"achieves":[99],"88%":[100],"mAP":[101],"on":[102],"our":[103],"dataset":[104],"at":[105],"11.6FPS,":[106],"which":[107],"has":[108],"good":[110],"effect.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}