{"id":"https://openalex.org/W4411726108","doi":"https://doi.org/10.1109/tvt.2025.3583760","title":"Sequential Descriptors for Visual Place Recognition: Combining EMLA Training With TFA-Net Aggregation","display_name":"Sequential Descriptors for Visual Place Recognition: Combining EMLA Training With TFA-Net Aggregation","publication_year":2025,"publication_date":"2025-06-27","ids":{"openalex":"https://openalex.org/W4411726108","doi":"https://doi.org/10.1109/tvt.2025.3583760"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2025.3583760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3583760","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Vehicular Technology","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/A5068841874","display_name":"Peng Li","orcid":"https://orcid.org/0009-0008-0794-5070"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Li","raw_affiliation_strings":["Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0009-0008-0794-5070","affiliations":[{"raw_affiliation_string":"Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129337","display_name":"Shuhuan Wen","orcid":"https://orcid.org/0000-0002-7646-4958"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhuan Wen","raw_affiliation_strings":["Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-7646-4958","affiliations":[{"raw_affiliation_string":"Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420016","display_name":"F. Richard Yu","orcid":"https://orcid.org/0000-0003-1006-7594"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"F. Richard Yu","raw_affiliation_strings":["Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0003-1006-7594","affiliations":[{"raw_affiliation_string":"Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055356431","display_name":"Tony Z. Qiu","orcid":"https://orcid.org/0000-0001-6120-3619"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tony Z. Qiu","raw_affiliation_strings":["Intelligent Transport System Research Center, Wuhan University of Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6120-3619","affiliations":[{"raw_affiliation_string":"Intelligent Transport System Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11257886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"74","issue":"12","first_page":"18385","last_page":"18395"},"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":0.9977999925613403,"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":0.9977999925613403,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.979200005531311,"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/training","display_name":"Training (meteorology)","score":0.5913771390914917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5231496095657349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5227853655815125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4959958493709564},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43029090762138367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36832869052886963},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35905420780181885},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34594377875328064},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3218647241592407}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5913771390914917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5231496095657349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5227853655815125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4959958493709564},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43029090762138367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36832869052886963},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35905420780181885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34594377875328064},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3218647241592407},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2025.3583760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3583760","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2827034588","display_name":null,"funder_award_id":"52172332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5191620234","display_name":null,"funder_award_id":"62273296","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":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2070724998","https://openalex.org/W2110405746","https://openalex.org/W2117228865","https://openalex.org/W2119605622","https://openalex.org/W2144824356","https://openalex.org/W2558027072","https://openalex.org/W2737165983","https://openalex.org/W2946583690","https://openalex.org/W2951019013","https://openalex.org/W2995140162","https://openalex.org/W2997164612","https://openalex.org/W3017044510","https://openalex.org/W3034213661","https://openalex.org/W3034258123","https://openalex.org/W3034275286","https://openalex.org/W3136246337","https://openalex.org/W3137393880","https://openalex.org/W3161770758","https://openalex.org/W3173736705","https://openalex.org/W3174803757","https://openalex.org/W3184915579","https://openalex.org/W4210786584","https://openalex.org/W4285044825","https://openalex.org/W4285298655","https://openalex.org/W4285742775","https://openalex.org/W4312317456","https://openalex.org/W4312854990","https://openalex.org/W4317794983","https://openalex.org/W4319300119","https://openalex.org/W4389819300","https://openalex.org/W4390659394","https://openalex.org/W4390933923","https://openalex.org/W4392931743","https://openalex.org/W4404544678","https://openalex.org/W4408181585"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4394050964","https://openalex.org/W2551249631"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,32,51,72,131],"present":[4],"a":[5,34,74],"novel":[6,35],"algorithm":[7],"aimed":[8],"at":[9],"enhancing":[10],"Visual":[11],"Place":[12],"Recognition":[13],"(VPR)":[14],"by":[15],"addressing":[16],"the":[17,38,58,135,144],"inherent":[18],"limitations":[19],"of":[20,97,137,147],"existing":[21],"sequence-based":[22],"methods.":[23],"Our":[24],"primary":[25],"contributions":[26],"encompass":[27],"three":[28],"key":[29],"areas:":[30],"firstly,":[31],"propose":[33],"training":[36],"approach,":[37],"Enhanced":[39],"Metric":[40],"Learning":[41],"Approach":[42],"(EMLA),":[43],"for":[44,156,166],"extracting":[45],"more":[46],"robust":[47],"global":[48],"descriptors;":[49],"secondly,":[50],"design":[52],"an":[53],"advanced":[54],"sequence":[55,138],"aggregation":[56],"method,":[57],"Temporal":[59],"Frame":[60],"Aggregation":[61],"Network":[62],"(TFA-Net),":[63],"that":[64,114],"effectively":[65],"integrates":[66],"information":[67],"from":[68],"image":[69,127],"sequences;":[70],"thirdly,":[71],"develop":[73],"similarity-based":[75],"descriptor":[76],"sorting":[77],"mechanism,":[78],"Cascade":[79],"Descriptor":[80,84],"Matching":[81],"with":[82],"Similarity-Based":[83],"Sorting":[85],"(CDM-SBDS),":[86],"to":[87],"improve":[88],"matching":[89],"accuracy":[90],"and":[91,108,142],"efficiency.":[92],"We":[93],"conducted":[94],"comprehensive":[95],"evaluations":[96],"our":[98,115,148],"proposed":[99],"methods":[100,116],"on":[101,140],"four":[102],"diverse":[103],"datasets:":[104],"Oxford,":[105],"Norland-SF,":[106],"Amman,":[107],"Austin.":[109],"The":[110],"experimental":[111],"results":[112,151],"demonstrate":[113],"consistently":[117],"perform":[118],"well":[119],"across":[120],"various":[121],"scenarios,":[122],"particularly":[123],"excel":[124],"in":[125,159],"large-scale":[126],"retrieval":[128],"tasks.":[129],"Additionally,":[130],"provide":[132],"insights":[133],"into":[134],"impact":[136],"length":[139],"performance":[141],"discuss":[143],"computational":[145],"efficiency":[146],"approach.":[149],"These":[150],"also":[152],"highlight":[153],"potential":[154],"areas":[155],"further":[157],"improvement":[158],"handling":[160],"complex":[161],"datasets,":[162],"providing":[163],"valuable":[164],"directions":[165],"future":[167],"research.":[168]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
