{"id":"https://openalex.org/W2793027867","doi":"https://doi.org/10.1504/ijhpcn.2016.10010714","title":"An automatic traffic-congestion detection method for bad weather based on traffic video","display_name":"An automatic traffic-congestion detection method for bad weather based on traffic video","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2793027867","doi":"https://doi.org/10.1504/ijhpcn.2016.10010714","mag":"2793027867"},"language":"en","primary_location":{"id":"doi:10.1504/ijhpcn.2016.10010714","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijhpcn.2016.10010714","pdf_url":null,"source":{"id":"https://openalex.org/S159903936","display_name":"International Journal of High Performance Computing and Networking","issn_l":"1740-0562","issn":["1740-0562","1740-0570"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of High Performance Computing and Networking","raw_type":"journal-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/A5054232978","display_name":"Jieren Cheng","orcid":"https://orcid.org/0000-0002-0160-0126"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jieren Cheng","raw_affiliation_strings":["Hainan University, 570228, Haikou, China; State Key Laboratory of Marine Resource Utilization in South China Sea, 570228, Haikou, China","State Key Laboratory of Marine Resource Utilization in South China Sea, 570228, Haikou, China","Hainan University, 570228, Haikou, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, 570228, Haikou, China; State Key Laboratory of Marine Resource Utilization in South China Sea, 570228, Haikou, China","institution_ids":["https://openalex.org/I20942203"]},{"raw_affiliation_string":"State Key Laboratory of Marine Resource Utilization in South China Sea, 570228, Haikou, China","institution_ids":[]},{"raw_affiliation_string":"Hainan University, 570228, Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5054232978"],"corresponding_institution_ids":["https://openalex.org/I20942203"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62533774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":"1","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9973999857902527,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9973999857902527,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9925000071525574,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/computer-science","display_name":"Computer science","score":0.757597029209137},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6327943801879883},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.6237120032310486},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6121731400489807},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.5828650593757629},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5023763179779053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2955949902534485},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2265014946460724},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21732163429260254},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.13017112016677856},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09147480130195618}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.757597029209137},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6327943801879883},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.6237120032310486},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6121731400489807},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.5828650593757629},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5023763179779053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2955949902534485},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2265014946460724},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21732163429260254},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.13017112016677856},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09147480130195618}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijhpcn.2016.10010714","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijhpcn.2016.10010714","pdf_url":null,"source":{"id":"https://openalex.org/S159903936","display_name":"International Journal of High Performance Computing and Networking","issn_l":"1740-0562","issn":["1740-0562","1740-0570"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of High Performance Computing and Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W46032129","https://openalex.org/W1620645064","https://openalex.org/W1762535390","https://openalex.org/W2007877577","https://openalex.org/W2042230250","https://openalex.org/W2048299340","https://openalex.org/W2061879449","https://openalex.org/W2072124501","https://openalex.org/W2080271103","https://openalex.org/W2086424610","https://openalex.org/W2108396781","https://openalex.org/W2116590921","https://openalex.org/W2125188192","https://openalex.org/W2147421915","https://openalex.org/W2152022916","https://openalex.org/W2170028728","https://openalex.org/W2288560581","https://openalex.org/W2336484677","https://openalex.org/W2344811709","https://openalex.org/W2380425296","https://openalex.org/W2393140808","https://openalex.org/W2394437202","https://openalex.org/W2417897405","https://openalex.org/W2536722097","https://openalex.org/W2740373864","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W301804496","https://openalex.org/W2042439812","https://openalex.org/W2972320057","https://openalex.org/W2897741166","https://openalex.org/W2988005308","https://openalex.org/W2973196987","https://openalex.org/W4386289889","https://openalex.org/W1669406372","https://openalex.org/W4211214322","https://openalex.org/W2077900203"],"abstract_inverted_index":{"The":[0],"result":[1],"of":[2,22,58,96,104,119],"automatic":[3,120],"traffic-congestion":[4],"detection":[5,20,123],"method":[6,21,33,49,78,92,114,128],"in":[7,72,124,133],"bad":[8,125,140],"weather":[9],"is":[10,108,138],"inaccurate.":[11],"In":[12],"response":[13],"to":[14,38,54],"this":[15,73,77],"situation,":[16],"we":[17],"propose":[18,64],"a":[19,65,130],"traffic":[23,67,87,97,105,121],"congestion":[24,68,88,98,122],"based":[25],"on":[26],"histogram":[27,51],"equalisation":[28,52],"and":[29,84,100],"discrete-frame":[30,35],"difference.":[31],"This":[32,127],"uses":[34],"difference":[36],"algorithm":[37,53,71],"extract":[39],"the":[40,48,56,59,82,86,91,94,102,113,116],"images":[41],"that":[42,112],"have":[43],"vehicle":[44,60],"information":[45],"firstly.":[46],"Then,":[47],"employs":[50],"eliminate":[55],"noise":[57],"images.":[61],"We":[62],"also":[63],"corresponding":[66],"index":[69,99],"statistical":[70],"step.":[74],"After":[75],"that,":[76],"recognises":[79],"vehicles":[80],"from":[81],"video":[83],"computes":[85],"index.":[89],"Finally,":[90],"transforms":[93],"dimension":[95],"obtains":[101],"state":[103],"congestion.":[106],"It":[107],"proved":[109],"by":[110],"experiments":[111],"increases":[115],"accuracy":[117],"rate":[118],"weather.":[126,141],"has":[129],"wonderful":[131],"prospect":[132],"some":[134],"areas":[135],"where":[136],"there":[137],"usually":[139]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}