{"id":"https://openalex.org/W4408527006","doi":"https://doi.org/10.1007/s44244-025-00024-2","title":"E-MobileViT: a lightweight model for traffic sign recognition","display_name":"E-MobileViT: a lightweight model for traffic sign recognition","publication_year":2025,"publication_date":"2025-03-17","ids":{"openalex":"https://openalex.org/W4408527006","doi":"https://doi.org/10.1007/s44244-025-00024-2"},"language":"en","primary_location":{"id":"doi:10.1007/s44244-025-00024-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44244-025-00024-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44244-025-00024-2.pdf","source":{"id":"https://openalex.org/S4387287974","display_name":"Industrial Artificial Intelligence","issn_l":"2731-667X","issn":["2731-667X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Industrial Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s44244-025-00024-2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114198043","display_name":"Shiqi Song","orcid":null},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Shiqi Song","raw_affiliation_strings":["School of Computer Science, The University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025044299","display_name":"Xinfeng Ye","orcid":"https://orcid.org/0000-0001-8483-2872"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Xinfeng Ye","raw_affiliation_strings":["School of Computer Science, The University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008264603","display_name":"Sathiamoorthy Manoharan","orcid":"https://orcid.org/0000-0003-4958-4185"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Sathiamoorthy Manoharan","raw_affiliation_strings":["School of Computer Science, The University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114198043"],"corresponding_institution_ids":["https://openalex.org/I154130895"],"apc_list":null,"apc_paid":null,"fwci":12.5954,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.98662604,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"3","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.6662431955337524},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5187042355537415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5186452269554138},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.49162131547927856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14162620902061462}],"concepts":[{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.6662431955337524},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5187042355537415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5186452269554138},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.49162131547927856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14162620902061462},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44244-025-00024-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44244-025-00024-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44244-025-00024-2.pdf","source":{"id":"https://openalex.org/S4387287974","display_name":"Industrial Artificial Intelligence","issn_l":"2731-667X","issn":["2731-667X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Industrial Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9d81c02b6c7d441ebb6f9992ec3cb29c","is_oa":true,"landing_page_url":"https://doaj.org/article/9d81c02b6c7d441ebb6f9992ec3cb29c","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":"Industrial Artificial Intelligence, Vol 3, Iss 1, Pp 1-15 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44244-025-00024-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44244-025-00024-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44244-025-00024-2.pdf","source":{"id":"https://openalex.org/S4387287974","display_name":"Industrial Artificial Intelligence","issn_l":"2731-667X","issn":["2731-667X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Industrial Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408527006.pdf"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1977610018","https://openalex.org/W2117876524","https://openalex.org/W2165849038","https://openalex.org/W2624283384","https://openalex.org/W2752782242","https://openalex.org/W2791496413","https://openalex.org/W2884585870","https://openalex.org/W2989219518","https://openalex.org/W3111897001","https://openalex.org/W3177052299","https://openalex.org/W3215846555","https://openalex.org/W4206510012","https://openalex.org/W4210667216","https://openalex.org/W4310605271","https://openalex.org/W4363675738","https://openalex.org/W4364379197","https://openalex.org/W4384037226","https://openalex.org/W4390695769","https://openalex.org/W4391848450","https://openalex.org/W4392969537","https://openalex.org/W6602646189","https://openalex.org/W6603884005","https://openalex.org/W6604344240"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4283820116","https://openalex.org/W4379231512","https://openalex.org/W4378699879","https://openalex.org/W3128164723","https://openalex.org/W4286647459","https://openalex.org/W2899819381","https://openalex.org/W2557202782","https://openalex.org/W3215426395","https://openalex.org/W2772251146"],"abstract_inverted_index":{"Abstract":[0],"Traffic":[1,85,91,97],"sign":[2,154],"recognition":[3,155],"is":[4,29,139],"crucial":[5],"for":[6,141,152],"intelligent":[7],"transportation":[8],"and":[9,15,40,48,70,95,102,108,114,124],"autonomous":[10],"driving,":[11],"ensuring":[12],"road":[13],"safety":[14],"efficient":[16],"traffic":[17,153],"management.":[18],"This":[19],"paper":[20],"proposes":[21],"a":[22,149],"lightweight":[23],"enhanced":[24],"MobileViT":[25,33],"model":[26,57,64,76,81,138],"(E-MobileViT).":[27],"It":[28],"based":[30],"on":[31,82],"the":[32,36,56,66,73,80,83,119],"model,":[34],"combining":[35],"advantages":[37],"of":[38,75,122],"CNN":[39],"Transformer.":[41],"We":[42,78,117],"integrate":[43],"Efficient":[44],"Local":[45],"Attention":[46,51],"(ELA)":[47],"Convolutional":[49],"Block":[50],"Module":[52],"(CBAM)":[53],"mechanisms":[54,126],"in":[55],"to":[58],"improve":[59],"feature":[60,67],"extraction.":[61],"The":[62],"proposed":[63],"improves":[65],"fusion":[68],"structure":[69],"significantly":[71],"reduces":[72],"number":[74],"parameters.":[77],"evaluated":[79],"German":[84],"Sign":[86],"Recognition":[87],"Benchmark":[88],"(GTSRB),":[89],"Belgian":[90],"Signs":[92,98],"Database":[93,99],"(BTSD),":[94],"China":[96],"(TSRD)":[100],"datasets":[101],"its":[103],"accuracy":[104],"reaches":[105],"99.61%,":[106],"99.26%":[107],"97.34%,":[109],"respectively,":[110],"which":[111],"outperforms":[112],"traditional":[113],"advanced":[115],"models.":[116],"confirmed":[118],"key":[120],"role":[121],"ELA":[123],"CBAM":[125],"through":[127],"ablation":[128],"experiments.":[129],"With":[130],"fewer":[131],"parameters":[132],"than":[133],"mainstream":[134],"models,":[135],"our":[136],"E-MobileViT":[137],"suitable":[140],"resource-constrained":[142],"environments":[143],"such":[144],"as":[145],"mobile":[146],"devices,":[147],"providing":[148],"balanced":[150],"solution":[151],"tasks.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9}],"updated_date":"2026-05-10T08:33:47.465468","created_date":"2025-10-10T00:00:00"}
