{"id":"https://openalex.org/W1965470957","doi":"https://doi.org/10.1109/ispa.2013.6703849","title":"Car recognition from frontal images in mobile environment","display_name":"Car recognition from frontal images in mobile environment","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W1965470957","doi":"https://doi.org/10.1109/ispa.2013.6703849","mag":"1965470957"},"language":"en","primary_location":{"id":"doi:10.1109/ispa.2013.6703849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","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/A5001091741","display_name":"Viktor Varjas","orcid":null},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Viktor Varjas","raw_affiliation_strings":["Department of Image Processing and Computer Graphics, University of Szeged, Hungary","Dept. of Image Process. & Comput. Graphics, Univ. of Szeged, Szeged, Hungary"],"affiliations":[{"raw_affiliation_string":"Department of Image Processing and Computer Graphics, University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]},{"raw_affiliation_string":"Dept. of Image Process. & Comput. Graphics, Univ. of Szeged, Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011474027","display_name":"Attila Tan\u00e1cs","orcid":null},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Attila Tanacs","raw_affiliation_strings":["Department of Image Processing and Computer Graphics, University of Szeged, Hungary","Dept. of Image Process. & Comput. Graphics, Univ. of Szeged, Szeged, Hungary"],"affiliations":[{"raw_affiliation_string":"Department of Image Processing and Computer Graphics, University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]},{"raw_affiliation_string":"Dept. of Image Process. & Comput. Graphics, Univ. of Szeged, Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001091741"],"corresponding_institution_ids":["https://openalex.org/I227486990"],"apc_list":null,"apc_paid":null,"fwci":1.9051,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.87196476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"819","last_page":"823"},"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":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9983999729156494,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983000159263611,"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":0.7973929047584534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.705534040927887},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6507488489151001},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5548207759857178},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5521864891052246},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5103592276573181},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45515626668930054},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4410164952278137},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42144787311553955},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4192529320716858},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4125165343284607},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3162100613117218}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973929047584534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.705534040927887},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6507488489151001},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5548207759857178},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5521864891052246},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5103592276573181},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45515626668930054},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4410164952278137},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42144787311553955},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4192529320716858},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4125165343284607},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3162100613117218},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispa.2013.6703849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","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":10,"referenced_works":["https://openalex.org/W1528417023","https://openalex.org/W1924485039","https://openalex.org/W2069428064","https://openalex.org/W2070935429","https://openalex.org/W2118707506","https://openalex.org/W2123203601","https://openalex.org/W2131490314","https://openalex.org/W2143799995","https://openalex.org/W4256253899","https://openalex.org/W6631647551"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2046456988","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Recognition":[0],"of":[1,64,98,121,132],"car":[2],"make":[3],"and":[4,36,67,70,94,101,109,129],"model":[5],"from":[6,33],"frontal":[7],"images":[8],"is":[9,38,48,77,86],"a":[10,43,116],"common":[11],"problem":[12],"in":[13,96],"computer":[14],"vision.":[15],"We":[16],"refined":[17],"existing":[18],"approaches":[19],"based":[20],"on":[21],"ROIs":[22],"defined":[23],"relative":[24],"to":[25,79,92,144],"the":[26,34,61,65,99,119,122,130,133],"number":[27],"plate.":[28],"Square-Mapped-Gradient":[29],"features":[30,135],"are":[31,136],"extracted":[32],"ROI":[35],"recognition":[37],"accomplished":[39],"by":[40,115],"classification":[41,76],"utilizing":[42],"learning":[44,123],"set.":[45],"The":[46,74],"classifier":[47],"evaluated":[49,60],"using":[50],"ground":[51],"truth":[52],"data":[53],"provided":[54],"manually.":[55],"Via":[56],"numerical":[57],"simulations":[58],"we":[59],"detection":[62],"tolerance":[63],"method":[66],"proposed":[68],"semi-automatic":[69,100],"fully":[71,102],"automatic":[72,103],"methods.":[73],"SMG-based":[75],"able":[78],"give":[80],"nearly":[81],"perfect":[82],"results":[83],"when":[84],"there":[85],"no":[87],"outlier":[88],"class,":[89],"which":[90],"decreases":[91],"92%":[93],"87%":[95],"case":[97],"methods,":[104],"respectively.":[105],"Separation":[106],"between":[107],"outliers":[108],"known":[110],"types":[111],"can":[112,125,140],"be":[113,126,141],"balanced":[114],"threshold.":[117],"Since":[118],"size":[120,131],"set":[124],"kept":[127],"low":[128],"SMG":[134],"small,":[137],"this":[138],"approach":[139],"successfully":[142],"used":[143],"solve":[145],"mobile":[146],"client-server":[147],"scenarios.":[148]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
