{"id":"https://openalex.org/W2093880446","doi":"https://doi.org/10.1117/12.2030883","title":"A visual saliency based method for vehicle logo detection","display_name":"A visual saliency based method for vehicle logo detection","publication_year":2013,"publication_date":"2013-07-19","ids":{"openalex":"https://openalex.org/W2093880446","doi":"https://doi.org/10.1117/12.2030883","mag":"2093880446"},"language":"en","primary_location":{"id":"doi:10.1117/12.2030883","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2030883","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100403428","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-0343-3499"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["Institute of Automation (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111520052","display_name":"Yiping Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Shen","raw_affiliation_strings":["Institute of Automation (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035418510","display_name":"Hongxing Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxing Chang","raw_affiliation_strings":["Institute of Automation (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210094879"],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49460623,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8878","issue":null,"first_page":"887833","last_page":"887833"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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":0.8731763958930969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8352594375610352},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.8062592148780823},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7722921371459961},{"id":"https://openalex.org/keywords/saliency-map","display_name":"Saliency map","score":0.761540412902832},{"id":"https://openalex.org/keywords/logo","display_name":"Logo (programming language)","score":0.7378060817718506},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.561543345451355},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5306723713874817},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4414343237876892},{"id":"https://openalex.org/keywords/template-matching","display_name":"Template matching","score":0.4245193898677826},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4219732880592346},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.415129691362381},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38042598962783813},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3737521767616272},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.302640438079834}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8731763958930969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8352594375610352},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8062592148780823},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7722921371459961},{"id":"https://openalex.org/C2779679900","wikidata":"https://www.wikidata.org/wiki/Q25304431","display_name":"Saliency map","level":3,"score":0.761540412902832},{"id":"https://openalex.org/C2778720087","wikidata":"https://www.wikidata.org/wiki/Q201436","display_name":"Logo (programming language)","level":2,"score":0.7378060817718506},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.561543345451355},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5306723713874817},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4414343237876892},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.4245193898677826},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4219732880592346},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.415129691362381},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38042598962783813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3737521767616272},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.302640438079834},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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":1,"locations":[{"id":"doi:10.1117/12.2030883","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2030883","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W1542224353","https://openalex.org/W2050699221","https://openalex.org/W2155191322","https://openalex.org/W4368227384","https://openalex.org/W2148060698","https://openalex.org/W2094999696","https://openalex.org/W1985373260","https://openalex.org/W2891205743","https://openalex.org/W2176101330"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,31],"novel":[4],"method":[5,28,83],"based":[6,34],"on":[7,35,65],"visual":[8],"saliency":[9,32,39,51],"and":[10,41,74,80],"template":[11,58],"matching":[12,59],"for":[13,85],"detecting":[14],"vehicle":[15],"logo":[16],"from":[17],"images":[18,69],"captured":[19],"by":[20,48],"cross-road":[21],"cameras.":[22],"To":[23],"detect":[24],"the":[25,36,50,62,77],"logo,":[26],"such":[27],"first":[29],"generates":[30],"map":[33],"modified":[37],"Itti\u2019s":[38],"model,":[40],"then":[42],"obtains":[43],"regions":[44],"of":[45,76],"interest":[46],"(ROI)":[47],"thresholding":[49],"map,":[52],"at":[53],"last":[54],"performs":[55],"an":[56],"edge-based":[57],"to":[60],"locate":[61],"logo.":[63],"Experiments":[64],"more":[66],"than":[67],"2400":[68],"validate":[70],"both":[71],"high":[72],"accuracy":[73],"efficiency":[75],"proposed":[78],"method,":[79],"demonstrates":[81],"our":[82],"suitable":[84],"real-time":[86],"application.":[87]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}