{"id":"https://openalex.org/W1976200221","doi":"https://doi.org/10.1109/icnc.2014.6975892","title":"Traffic congestion judgment based on linear spatial pyramid matching using sparse coding","display_name":"Traffic congestion judgment based on linear spatial pyramid matching using sparse coding","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W1976200221","doi":"https://doi.org/10.1109/icnc.2014.6975892","mag":"1976200221"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2014.6975892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","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/A5110457400","display_name":"Long Zhou","orcid":"https://orcid.org/0000-0003-4538-6827"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Zhou","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036253906","display_name":"Luping Ji","orcid":"https://orcid.org/0000-0002-1200-5218"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luping Ji","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":null,"display_name":"Deshui Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deshui Hao","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05396781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"540","last_page":"544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9954000115394592,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9940000176429749,"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/judgement","display_name":"Judgement","score":0.8013119697570801},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6569080352783203},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5840955972671509},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5835832357406616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4902961552143097},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.4721035063266754},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4627739191055298},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45655977725982666},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.42487964034080505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3994862735271454},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35484495759010315},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3090021312236786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16675743460655212},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15647900104522705},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.12743282318115234}],"concepts":[{"id":"https://openalex.org/C2776548248","wikidata":"https://www.wikidata.org/wiki/Q12621536","display_name":"Judgement","level":2,"score":0.8013119697570801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6569080352783203},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5840955972671509},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5835832357406616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4902961552143097},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.4721035063266754},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4627739191055298},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45655977725982666},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.42487964034080505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3994862735271454},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35484495759010315},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3090021312236786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16675743460655212},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15647900104522705},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.12743282318115234},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2014.6975892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1931526510","https://openalex.org/W2014013321","https://openalex.org/W2022735534","https://openalex.org/W2097018403","https://openalex.org/W2107034620","https://openalex.org/W2148596671","https://openalex.org/W2153663612","https://openalex.org/W2161516371","https://openalex.org/W2162915993","https://openalex.org/W2166742463","https://openalex.org/W6674642818","https://openalex.org/W6683660953"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2886802431","https://openalex.org/W4388216822","https://openalex.org/W2247121321","https://openalex.org/W1761762290","https://openalex.org/W2391926582","https://openalex.org/W4391191813","https://openalex.org/W2049930962"],"abstract_inverted_index":{"Traffic":[0],"congestion":[1,23,54],"judgement":[2,16,107],"is":[3,26,55,112],"a":[4,15],"frequently":[5],"addressed":[6],"problem":[7],"in":[8,67,75],"intelligent":[9],"transportation":[10],"system.":[11],"In":[12],"this":[13,68,72],"paper,":[14],"algorithm":[17,30,108],"for":[18],"identifying":[19],"the":[20,32,41,53,79,82,99,106,118],"occurring":[21,56],"traffic":[22],"of":[24,61,81],"vehicles":[25,39],"experimentally":[27],"designed.":[28],"This":[29],"extracts":[31],"SIFT":[33],"features":[34],"from":[35],"an":[36],"image":[37],"containing":[38],"using":[40,46],"linear":[42],"spatial":[43],"pyramid":[44],"matching":[45],"sparse":[47],"coding":[48],"(ScSPM),":[49],"then":[50],"judges":[51],"weather":[52],"or":[57],"not.":[58],"A":[59],"number":[60],"experiments":[62],"are":[63,96],"conducted":[64],"and":[65,94,114],"compared":[66],"paper":[69],"to":[70,77],"evaluate":[71],"algorithm.":[73],"However,":[74],"order":[76],"compare":[78],"performance":[80],"proposed":[83],"ScSPM":[84,111],"operator":[85],"with":[86],"some":[87],"others,":[88],"two":[89],"classic":[90],"classification":[91],"algorithms":[92],"SVM":[93],"SPM":[95],"used":[97],"as":[98],"references.":[100],"Through":[101],"these":[102],"comparisons":[103],"show":[104],"that":[105],"based":[109],"on":[110],"efficient":[113],"performs":[115],"better":[116],"than":[117],"other":[119],"two.":[120]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}