{"id":"https://openalex.org/W4384080177","doi":"https://doi.org/10.1109/access.2023.3294689","title":"Transfer Learning for Region-Wide Trajectory Outlier Detection","display_name":"Transfer Learning for Region-Wide Trajectory Outlier Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4384080177","doi":"https://doi.org/10.1109/access.2023.3294689"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3294689","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3294689","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10179898.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":null,"license_id":null,"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/ielx7/6287639/6514899/10179898.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050314527","display_name":"Yueyang Su","orcid":"https://orcid.org/0000-0002-6154-8059"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyang Su","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-6154-8059","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070236880","display_name":"Di Yao","orcid":"https://orcid.org/0000-0003-1778-8319"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Yao","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0003-1778-8319","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419125","display_name":"Tian Tian","orcid":"https://orcid.org/0000-0002-6044-9083"},"institutions":[{"id":"https://openalex.org/I4210153872","display_name":"Jiangsu Maritime Institute","ror":"https://ror.org/04pekda06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Tian","raw_affiliation_strings":["Nanjing Marine Radar Institute, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Marine Radar Institute, Nanjing, China","institution_ids":["https://openalex.org/I4210153872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109676956","display_name":"Jingping Bi","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingping Bi","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2637,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63205652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"11","issue":null,"first_page":"97001","last_page":"97013"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9976000189781189,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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":0.6775587797164917},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6342458128929138},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.602368175983429},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5864578485488892},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5067995190620422},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.42263680696487427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3285469114780426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775587797164917},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6342458128929138},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.602368175983429},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5864578485488892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5067995190620422},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.42263680696487427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3285469114780426},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3294689","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3294689","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10179898.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9ad5e82bb31445d299f2d4e1073066d0","is_oa":true,"landing_page_url":"https://doaj.org/article/9ad5e82bb31445d299f2d4e1073066d0","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 11, Pp 97001-97013 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3294689","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3294689","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10179898.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G1025052068","display_name":null,"funder_award_id":"62002343","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6470113806","display_name":null,"funder_award_id":"6207704","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384080177.pdf","grobid_xml":"https://content.openalex.org/works/W4384080177.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1999205465","https://openalex.org/W2028219125","https://openalex.org/W2046466133","https://openalex.org/W2085269948","https://openalex.org/W2100330570","https://openalex.org/W2102176141","https://openalex.org/W2126194848","https://openalex.org/W2136975357","https://openalex.org/W2153523687","https://openalex.org/W2514056879","https://openalex.org/W2601893308","https://openalex.org/W2734775449","https://openalex.org/W2767297659","https://openalex.org/W2767923185","https://openalex.org/W2775742549","https://openalex.org/W2783344919","https://openalex.org/W2789485833","https://openalex.org/W2808767391","https://openalex.org/W2897355009","https://openalex.org/W2898403153","https://openalex.org/W2900728397","https://openalex.org/W2902304528","https://openalex.org/W2907492528","https://openalex.org/W2910314742","https://openalex.org/W2912112202","https://openalex.org/W2912986282","https://openalex.org/W2913814504","https://openalex.org/W2944851425","https://openalex.org/W2947464817","https://openalex.org/W2948978827","https://openalex.org/W2949362468","https://openalex.org/W2949713224","https://openalex.org/W2952493731","https://openalex.org/W2955869622","https://openalex.org/W2979625610","https://openalex.org/W2985260327","https://openalex.org/W3021173937","https://openalex.org/W3029191757","https://openalex.org/W3043674422","https://openalex.org/W3047884290","https://openalex.org/W3091873932","https://openalex.org/W3107149409","https://openalex.org/W3116657254","https://openalex.org/W3116987847","https://openalex.org/W3117098906","https://openalex.org/W3120795858","https://openalex.org/W3130499959","https://openalex.org/W3134624922","https://openalex.org/W4205778173","https://openalex.org/W4213101961","https://openalex.org/W4224322699","https://openalex.org/W4226424593","https://openalex.org/W4283366068","https://openalex.org/W4287689466","https://openalex.org/W4290927679","https://openalex.org/W4385245566","https://openalex.org/W4391235284","https://openalex.org/W6739901393","https://openalex.org/W6756925667","https://openalex.org/W6763203961","https://openalex.org/W6765581236","https://openalex.org/W6781905506","https://openalex.org/W6850401463"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W2046456988","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Trajectory":[0],"outlier":[1],"detection":[2],"is":[3,21,106],"a":[4,65,84,109,134,161],"crucial":[5],"task":[6],"in":[7,27,39,51,67,80,93,147],"trajectory":[8,72,153,247],"data":[9,97,179],"mining":[10],"and":[11,220,233,249],"has":[12,59],"received":[13,61],"significant":[14],"attention.":[15],"However,":[16],"the":[17,68,115,123,138,143,152,167,172,178,194,199,205,211,217,221,225,250,260],"distribution":[18],"of":[19,71,119,181,213],"trajectories":[20],"tied":[22],"to":[23,48,107,122,141,170,197,235],"social":[24],"activities,":[25],"resulting":[26],"extreme":[28],"unevenness":[29],"among":[30,101,184],"regions.":[31,102,223],"While":[32],"existing":[33],"methods":[34],"have":[35],"demonstrated":[36],"excellent":[37],"performance":[38,257],"regions":[40,52,94,121,149,219],"with":[41,53,76,95,155,259],"sufficient":[42],"historical":[43],"trajectories,":[44],"they":[45],"frequently":[46],"struggle":[47],"detect":[49,91,236],"outliers":[50,92],"limited":[54],"trajectories.":[55],"Unfortunately,":[56],"this":[57,77,81],"issue":[58,208],"not":[60],"much":[62],"attention,":[63],"leaving":[64],"gap":[66,212],"current":[69],"understanding":[70],"mining.":[73],"To":[74,129],"deal":[75],"problem,":[78],"we":[79,132,159,186,239],"paper":[82],"propose":[83,160],"model":[85,136],"called":[86,137],"TTOD":[87,254],"that":[88,113,164,253],"can":[89,229],"effectively":[90],"sparse":[96],"by":[98,150,210],"transferring":[99],"knowledge":[100],"The":[103],"main":[104],"idea":[105],"learn":[108,142,171],"feature":[110,117,127,145,174,182,201,214,227],"mapping":[111,168],"function":[112,169],"maps":[114],"global":[116,144],"space":[118,146,228],"auxiliary":[120,148,218],"target":[124,173,200,222,226],"region\u2019s":[125],"specific":[126],"space.":[128,175],"achieve":[130],"this,":[131],"adopt":[133],"VAE-based":[135],"Global":[139],"VAE":[140,163],"modeling":[151],"patterns":[154],"Gaussian":[156],"distributions.":[157],"Then,":[158],"Specific-region":[162],"serves":[165],"as":[166],"Additionally,":[176],"considering":[177],"drift":[180],"distributions":[183,215],"regions,":[185],"introduced":[187],"an":[188],"additional":[189],"pattern":[190,206],"synthesis":[191],"layer,":[192],"named":[193],"De-drift":[195],"Layer,":[196],"diversify":[198],"space,":[202],"thus":[203],"addressing":[204],"missing":[207],"caused":[209],"between":[216],"Then":[224],"be":[230],"well":[231],"studied":[232],"applied":[234],"outliers.":[237],"Finally,":[238],"conduct":[240],"extensive":[241],"experiments":[242],"on":[243],"two":[244],"real":[245],"taxi":[246],"datasets":[248],"results":[251],"show":[252],"achieves":[255],"state-of-the-art":[256],"compared":[258],"baselines.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
