{"id":"https://openalex.org/W2407901846","doi":null,"title":"Vehicle logo recognition by spatial-SIFT combined with logistic regression","display_name":"Vehicle logo recognition by spatial-SIFT combined with logistic regression","publication_year":2016,"publication_date":"2016-07-05","ids":{"openalex":"https://openalex.org/W2407901846","mag":"2407901846"},"language":"en","primary_location":{"id":"pmh:oai:eprints.whiterose.ac.uk:99743","doi":null,"is_oa":true,"landing_page_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","pdf_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013248692","display_name":"Ruilong Chen","orcid":"https://orcid.org/0000-0002-7855-4711","observed_orcids":["https://orcid.org/0000-0002-7855-4711"]},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ruilong Chen","raw_affiliation_strings":["Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK"],"raw_orcid":"https://orcid.org/0000-0002-7855-4711","affiliations":[{"raw_affiliation_string":"Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045716647","display_name":"Matthew Hawes","orcid":"https://orcid.org/0000-0002-3742-3416","observed_orcids":["https://orcid.org/0000-0002-3742-3416"]},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Matthew Hawes","raw_affiliation_strings":["Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK"],"raw_orcid":"https://orcid.org/0000-0002-3742-3416","affiliations":[{"raw_affiliation_string":"Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006505402","display_name":"Lyudmila S. Mihaylova","orcid":"https://orcid.org/0000-0001-5856-2223","observed_orcids":["https://orcid.org/0000-0001-5856-2223"]},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lyudmila Mihaylova","raw_affiliation_strings":["Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK"],"raw_orcid":"https://orcid.org/0000-0001-5856-2223","affiliations":[{"raw_affiliation_string":"Department of Automatic Control and Systems Engineering, University of Sheffield S1 3JD, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039704967","display_name":"Jingjing Xiao","orcid":"https://orcid.org/0000-0001-5020-638X","observed_orcids":["https://orcid.org/0000-0001-5020-638X"]},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jingjing Xiao","raw_affiliation_strings":["School of Electronics, Electrical and Computer Engineering, University of Birmingham, B15 2TT, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics, Electrical and Computer Engineering, University of Birmingham, B15 2TT, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062908102","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-2968-2888","observed_orcids":["https://orcid.org/0000-0003-2968-2888","https://orcid.org/0000-0003-2860-1783"]},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, University of Sheffield, S1 3JD, UK"],"raw_orcid":"https://orcid.org/0000-0003-2968-2888","affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, University of Sheffield, S1 3JD, UK","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6682,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82144865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1228","last_page":"1235"},"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":0.9818999767303467,"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":0.9818999767303467,"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":0.0071000000461936,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.006300000008195639,"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/vehicle-logo-recognition","display_name":"vehicle logo recognition","score":0.996999979019165},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"scale-invariant feature transform","score":0.8230000138282776},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.8199999928474426},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"histogram of oriented gradients","score":0.8109999895095825},{"id":"https://openalex.org/keywords/feature-representation","display_name":"feature representation","score":0.7929999828338623},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.6710000038146973},{"id":"https://openalex.org/keywords/noise-robustness","display_name":"noise robustness","score":0.8199999928474426}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.8931052684783936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7805100679397583},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7575539350509644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6655721068382263},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6464349031448364},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6179342269897461},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5836119651794434},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5531731843948364},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5165125727653503},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.516323983669281},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.47189056873321533},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4353744387626648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3355902433395386},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3313007950782776},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16172140836715698},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:eprints.whiterose.ac.uk:99743","doi":null,"is_oa":true,"landing_page_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","pdf_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"},{"id":"mag:2407901846","doi":null,"is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/fusion/fusion2016.html#ChenHMXL16","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Information Fusion","raw_type":null}],"best_oa_location":{"id":"pmh:oai:eprints.whiterose.ac.uk:99743","doi":null,"is_oa":true,"landing_page_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","pdf_url":"http://eprints.whiterose.ac.uk/99743/1/PID4139805.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2407901846.pdf","grobid_xml":"https://content.openalex.org/works/W2407901846.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1595303882","https://openalex.org/W1625255723","https://openalex.org/W1663973292","https://openalex.org/W1981976602","https://openalex.org/W2003813371","https://openalex.org/W2004859495","https://openalex.org/W2006544565","https://openalex.org/W2012942264","https://openalex.org/W2016120301","https://openalex.org/W2034609692","https://openalex.org/W2042421713","https://openalex.org/W2042500594","https://openalex.org/W2058459606","https://openalex.org/W2066589505","https://openalex.org/W2066941820","https://openalex.org/W2075057232","https://openalex.org/W2080829704","https://openalex.org/W2089665028","https://openalex.org/W2095758197","https://openalex.org/W2111688141","https://openalex.org/W2122111042","https://openalex.org/W2124450022","https://openalex.org/W2127218421","https://openalex.org/W2131846894","https://openalex.org/W2132254548","https://openalex.org/W2139323304","https://openalex.org/W2150579376","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2159727956","https://openalex.org/W2161969291","https://openalex.org/W2162915993"],"related_works":["https://openalex.org/W2058459606","https://openalex.org/W2749798860","https://openalex.org/W2110177572","https://openalex.org/W2885874466","https://openalex.org/W2139323304","https://openalex.org/W2087380349","https://openalex.org/W2516732592","https://openalex.org/W2025930809","https://openalex.org/W2885717105","https://openalex.org/W2124450022"],"abstract_inverted_index":{"An":[0],"efficient":[1],"recognition":[2],"framework":[3,18,39],"requires":[4],"both":[5,102],"\\ngood":[6],"feature":[7],"representation":[8],"and":[9,59],"effective":[10],"classification":[11,81],"methods.":[12,90],"\\nThis":[13],"paper":[14],"proposes":[15],"such":[16],"a":[17,21,30,80],"based":[19,47],"on":[20,48],"spatial":[22],"Scale":[23],"\\nInvariant":[24],"Feature":[25],"Transform":[26],"(SIFT)":[27],"combined":[28],"with":[29],"logistic":[31],"\\nregression":[32],"classifier.":[33],"The":[34],"performance":[35],"of":[36,44,51,83],"the":[37,49,66,75,92],"proposed":[38,76,93],"\\nis":[40],"compared":[41],"to":[42],"that":[43,74],"state-of-the-art":[45],"methods":[46],"\\nHistogram":[50],"Orientation":[52],"Gradients,":[53],"SIFT":[54],"features,":[55],"Support":[56],"\\nVector":[57],"Machine":[58],"K-Nearest":[60],"Neighbours":[61],"classifiers.":[62],"By":[63],"testing":[64,105],"\\nwith":[65],"largest":[67],"vehicle":[68],"logo":[69],"data-set,":[70],"it":[71],"is":[72,99],"shown":[73],"\\nframework":[77,94],"can":[78],"achieve":[79],"accuracy":[82],"99.93%,":[84],"\\nthe":[85],"best":[86],"among":[87],"all":[88],"studied":[89],"Moreover,":[91],"shows":[95],"robustness":[96],"when":[97],"noise":[98],"added":[100],"in":[101],"training":[103],"\\nand":[104],"images.":[106]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2016-06-24T00:00:00"}