{"id":"https://openalex.org/W7135383787","doi":"https://doi.org/10.1016/j.neucom.2026.133275","title":"Semi-supervised driving style recognition via deep metric learning and liquid time-constant networks","display_name":"Semi-supervised driving style recognition via deep metric learning and liquid time-constant networks","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7135383787","doi":"https://doi.org/10.1016/j.neucom.2026.133275"},"language":"en","primary_location":{"id":"doi:10.1016/j.neucom.2026.133275","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.neucom.2026.133275","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","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/A5073897730","display_name":"Shangwu Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangwu Jiang","raw_affiliation_strings":["The School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0000-8819-4484","affiliations":[{"raw_affiliation_string":"The School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ruochen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruochen Wang","raw_affiliation_strings":["The School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Renkai Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renkai Ding","raw_affiliation_strings":["The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129264298","display_name":"Qing Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Ye","raw_affiliation_strings":["The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129110948","display_name":"Yingfeng Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfeng Cai","raw_affiliation_strings":["The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":{"value":2470,"currency":"USD","value_usd":2470},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56235981,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"682","issue":null,"first_page":"133275","last_page":"133275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10363","display_name":"Low-power high-performance VLSI design","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11417","display_name":"Advancements in PLL and VCO Technologies","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/metric","display_name":"Metric (unit)","score":0.7106999754905701},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6751999855041504},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6460999846458435},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5724999904632568},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5543000102043152},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5364999771118164},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5273000001907349},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4814000129699707},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.46959999203681946}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8151000142097473},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7106999754905701},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6751999855041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6624000072479248},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6460999846458435},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6258000135421753},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5724999904632568},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5543000102043152},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5273000001907349},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.46959999203681946},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.438400000333786},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.33709999918937683},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27059999108314514}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.neucom.2026.133275","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.neucom.2026.133275","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5466403961181641,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2160595088","https://openalex.org/W2172717914","https://openalex.org/W2745090846","https://openalex.org/W2746721413","https://openalex.org/W2916651910","https://openalex.org/W2920594132","https://openalex.org/W2944851425","https://openalex.org/W2976682141","https://openalex.org/W3109334963","https://openalex.org/W3111364346","https://openalex.org/W3126174111","https://openalex.org/W3153872914","https://openalex.org/W3204836041","https://openalex.org/W4286559960","https://openalex.org/W4307457783","https://openalex.org/W4385452972","https://openalex.org/W4400678885","https://openalex.org/W4403193167"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-03-31T06:02:25.137627","created_date":"2026-03-15T00:00:00"}
