{"id":"https://openalex.org/W3035489328","doi":"https://doi.org/10.1109/access.2020.3001294","title":"Scene Attribute Semantic Relational Regularization for Transport-Travel Scene Understanding","display_name":"Scene Attribute Semantic Relational Regularization for Transport-Travel Scene Understanding","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3035489328","doi":"https://doi.org/10.1109/access.2020.3001294","mag":"3035489328"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3001294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3001294","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09113277.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09113277.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110758901","display_name":"Xin Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127216","display_name":"Ministry of Transport","ror":"https://ror.org/031wq1t38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216"]},{"id":"https://openalex.org/I4210139553","display_name":"Research Institute of Highway","ror":"https://ror.org/0335kqk33","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216","https://openalex.org/I4210139553"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Lei Wei","raw_affiliation_strings":["Research Institute of Highway Ministry of Transport, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3450-0102","affiliations":[{"raw_affiliation_string":"Research Institute of Highway Ministry of Transport, Beijing, China","institution_ids":["https://openalex.org/I4210139553","https://openalex.org/I4210127216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041576702","display_name":"Ruifen Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163873","display_name":"Zhengzhou University of Industrial Technology","ror":"https://ror.org/05es8as59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163873"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruifen Cheng","raw_affiliation_strings":["School of Management, Zhengzhou University of Industrial Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management, Zhengzhou University of Industrial Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I4210163873"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033927577","display_name":"Yingji Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127216","display_name":"Ministry of Transport","ror":"https://ror.org/031wq1t38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216"]},{"id":"https://openalex.org/I4210139553","display_name":"Research Institute of Highway","ror":"https://ror.org/0335kqk33","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216","https://openalex.org/I4210139553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingji Liu","raw_affiliation_strings":["Research Institute of Highway Ministry of Transport, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of Highway Ministry of Transport, Beijing, China","institution_ids":["https://openalex.org/I4210139553","https://openalex.org/I4210127216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033132937","display_name":"Wei Zhou","orcid":"https://orcid.org/0000-0002-0388-5292"},"institutions":[{"id":"https://openalex.org/I4210127216","display_name":"Ministry of Transport","ror":"https://ror.org/031wq1t38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216"]},{"id":"https://openalex.org/I4210139553","display_name":"Research Institute of Highway","ror":"https://ror.org/0335kqk33","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216","https://openalex.org/I4210139553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhou","raw_affiliation_strings":["Research Institute of Highway Ministry of Transport, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of Highway Ministry of Transport, Beijing, China","institution_ids":["https://openalex.org/I4210139553","https://openalex.org/I4210127216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052586688","display_name":"Daxin Tian","orcid":"https://orcid.org/0000-0001-7796-5650"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daxin Tian","raw_affiliation_strings":["School of Transportation Science and Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7796-5650","affiliations":[{"raw_affiliation_string":"School of Transportation Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5110758901"],"corresponding_institution_ids":["https://openalex.org/I4210127216","https://openalex.org/I4210139553"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.05524734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"118083","last_page":"118100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987000226974487,"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/crowds","display_name":"Crowds","score":0.8561795949935913},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8134771585464478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5187454223632812},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4798264503479004},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.336501806974411},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.333885133266449}],"concepts":[{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.8561795949935913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8134771585464478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5187454223632812},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4798264503479004},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.336501806974411},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.333885133266449},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3001294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3001294","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09113277.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:35767050993543bfa6545d389b683201","is_oa":true,"landing_page_url":"https://doaj.org/article/35767050993543bfa6545d389b683201","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 118083-118100 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3001294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3001294","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09113277.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2668996079","display_name":null,"funder_award_id":"61822101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4988131113","display_name":null,"funder_award_id":"4181002","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G7263983918","display_name":null,"funder_award_id":"61672082","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035489328.pdf","grobid_xml":"https://content.openalex.org/works/W3035489328.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W48884151","https://openalex.org/W1522734439","https://openalex.org/W1566135517","https://openalex.org/W1896424170","https://openalex.org/W1917639532","https://openalex.org/W1924160326","https://openalex.org/W1956595878","https://openalex.org/W1962468782","https://openalex.org/W1969914528","https://openalex.org/W1995766682","https://openalex.org/W2020746636","https://openalex.org/W2032612424","https://openalex.org/W2032699694","https://openalex.org/W2034812065","https://openalex.org/W2070148066","https://openalex.org/W2098411764","https://openalex.org/W2099528205","https://openalex.org/W2112055291","https://openalex.org/W2134670479","https://openalex.org/W2164990725","https://openalex.org/W2191616647","https://openalex.org/W2211992430","https://openalex.org/W2436685139","https://openalex.org/W2475223347","https://openalex.org/W2486988444","https://openalex.org/W2491457278","https://openalex.org/W2556382245","https://openalex.org/W2592051407","https://openalex.org/W2602645093","https://openalex.org/W2604735539","https://openalex.org/W2605124728","https://openalex.org/W2615278119","https://openalex.org/W2739606892","https://openalex.org/W2950673314","https://openalex.org/W2962786991","https://openalex.org/W2963094609","https://openalex.org/W2963373069","https://openalex.org/W2963677766","https://openalex.org/W2964430164","https://openalex.org/W2965166097","https://openalex.org/W2982586843","https://openalex.org/W2984809863","https://openalex.org/W2991813857","https://openalex.org/W3034984754","https://openalex.org/W3104752576","https://openalex.org/W6639495226","https://openalex.org/W6641069144","https://openalex.org/W6679792166","https://openalex.org/W6730368104","https://openalex.org/W6735781722","https://openalex.org/W6754005058","https://openalex.org/W6774408606"],"related_works":["https://openalex.org/W4240200267","https://openalex.org/W1511510665","https://openalex.org/W2154955495","https://openalex.org/W1524661185","https://openalex.org/W2078823605","https://openalex.org/W2500095415","https://openalex.org/W2097922264","https://openalex.org/W1997780040","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Attribute":[0,164,217,230],"learning":[1],"has":[2,241],"improved":[3,209],"the":[4,37,47,73,82,126,134,137,142,162,171,180,189,198,205,215,228,238,248,255,258],"performance":[5,243,256],"in":[6,23],"scene":[7,10,26,83,99,105,114,145,151,157,175,193,267],"understanding":[8],"and":[9,27,68,112,147,168,186,188,212,219,232,268],"recognition.":[11],"However,":[12,170],"there":[13,32],"are":[14,33,50,123,139,208],"many":[15],"attributes":[16,84],"described":[17],"by":[18,125,161,210],"words":[19],"or":[20],"short":[21],"texts":[22],"a":[24,59,91,110],"static":[25,143,155,265],"traffic":[28],"crowd":[29,192,271],"scene.":[30,272],"If":[31],"two":[34,48],"similar":[35],"scenes,":[36],"semantic":[38,60,65,85,94,101,106,120],"relationship":[39,96],"topology":[40,62],"structures":[41],"of":[42,46,204,247,257],"corresponding":[43],"attribute":[44,93,100,119],"groups":[45],"scenes":[49],"also":[51],"homogeneity.":[52],"But":[53],"it":[54],"is":[55,159,177,195,262],"difficult":[56],"to":[57,132,245],"learn":[58],"relation":[61],"projection":[63],"across":[64],"text":[66],"data":[67],"visual":[69],"data.":[70],"To":[71],"solve":[72],"problem,":[74],"we":[75,89],"construct":[76],"approximate":[77],"homeomorphism":[78],"mapping":[79],"based":[80,98,117],"on":[81,118,141,214,227],"relational":[86],"regularization.":[87],"Hence,":[88],"propose":[90],"novel":[92],"topological":[95],"regularization":[97],"learning(ARSL)":[102],"method":[103,207,261],"for":[104],"understanding.":[107],"We":[108],"establish":[109],"transport":[111],"travel":[113],"recognition":[115],"model":[116],"features":[121],"which":[122],"achieved":[124],"proposed":[127,135,206,239,259],"ARSL":[128,260],"algorithm.":[129],"In":[130],"order":[131],"verify":[133],"method,":[136],"experiments":[138],"implemented":[140],"transport-travel":[144,149,156,173,191,266,270],"dataset":[146,152,158,165,176,183,194,218,222,231,235],"dynamic":[148,172,190,269],"crowds":[150,174],"respectively.":[153,223],"The":[154,202,224],"constructed":[160,178],"SUN":[163,216,229],"including":[166,184],"images":[167],"texts.":[169],"through":[179],"WWW":[181,199,220,233],"Crowd":[182],"videos":[185],"texts,":[187],"named":[196],"as":[197],"Crowd-Sub":[200,221,234],"dataset.":[201],"performances":[203],"38.48%":[211],"17.51%":[213],"experimental":[225],"results":[226],"demonstrate":[236],"that":[237,254],"approach":[240],"superior":[242],"compared":[244],"state":[246],"art.":[249],"It":[250],"can":[251],"be":[252],"demonstrated":[253],"effective":[263],"against":[264]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}