{"id":"https://openalex.org/W4386056752","doi":"https://doi.org/10.1016/j.jai.2023.08.002","title":"Leveraging on few-shot learning for tire pattern classification in forensics","display_name":"Leveraging on few-shot learning for tire pattern classification in forensics","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4386056752","doi":"https://doi.org/10.1016/j.jai.2023.08.002"},"language":"en","primary_location":{"id":"doi:10.1016/j.jai.2023.08.002","doi":"https://doi.org/10.1016/j.jai.2023.08.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jai.2023.08.002","pdf_url":null,"source":{"id":"https://openalex.org/S4387285287","display_name":"Journal of Automation and Intelligence","issn_l":"2949-8554","issn":["2949-8554"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","oarl"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Automation and Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.jai.2023.08.002","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112394930","display_name":"Lijun Jiang","orcid":"https://orcid.org/0000-0002-6499-9760","observed_orcids":["https://orcid.org/0000-0002-6499-9760","https://orcid.org/0009-0004-4026-4083","https://orcid.org/0000-0002-7391-6322"]},"institutions":[{"id":"https://openalex.org/I188716491","display_name":"Republic Polytechnic","ror":"https://ror.org/04qf03327","country_code":"SG","type":"education","lineage":["https://openalex.org/I188716491"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Lijun Jiang","raw_affiliation_strings":["School of Engineering, Republic Polytechnic, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Republic Polytechnic, Singapore","institution_ids":["https://openalex.org/I188716491"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080196483","display_name":"Syed Ariff Syed Hesham","orcid":"https://orcid.org/0009-0000-9589-3056","observed_orcids":["https://orcid.org/0009-0000-9589-3056"]},"institutions":[{"id":"https://openalex.org/I188716491","display_name":"Republic Polytechnic","ror":"https://ror.org/04qf03327","country_code":"SG","type":"education","lineage":["https://openalex.org/I188716491"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Syed Ariff Syed Hesham","raw_affiliation_strings":["School of Engineering, Republic Polytechnic, Singapore"],"raw_orcid":"https://orcid.org/0009-0000-9589-3056","affiliations":[{"raw_affiliation_string":"School of Engineering, Republic Polytechnic, Singapore","institution_ids":["https://openalex.org/I188716491"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100896877","display_name":"Keng Pang Lim","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keng Pang Lim","raw_affiliation_strings":["Maschine Technology Pte. Ltd, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maschine Technology Pte. Ltd, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344158","display_name":"Changyun Wen","orcid":"https://orcid.org/0000-0001-9530-360X","observed_orcids":["https://orcid.org/0000-0001-9530-360X"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Changyun Wen","raw_affiliation_strings":["School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5080196483"],"corresponding_institution_ids":["https://openalex.org/I188716491"],"apc_list":{"value":0,"currency":"USD","value_usd":0},"apc_paid":null,"fwci":0.2136,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.47958398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"2","issue":"3","first_page":"146","last_page":"151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6327999830245972,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6327999830245972,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3041999936103821,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.011599999852478504,"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/few-shot-learning","display_name":"few-shot learning","score":0.8230000138282776},{"id":"https://openalex.org/keywords/meta-learning","display_name":"meta-learning","score":0.9369999766349792},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.843999981880188},{"id":"https://openalex.org/keywords/crime-scene-evidence","display_name":"crime scene evidence","score":0.7179999947547913}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7085163593292236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705344557762146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.703772783279419},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6599525809288025},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5849916338920593},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5843624472618103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4517306089401245},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41059610247612},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3831949234008789},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33552029728889465}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/j.jai.2023.08.002","doi":"https://doi.org/10.1016/j.jai.2023.08.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jai.2023.08.002","pdf_url":null,"source":{"id":"https://openalex.org/S4387285287","display_name":"Journal of Automation and Intelligence","issn_l":"2949-8554","issn":["2949-8554"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","oarl"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Automation and Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9cf9c56aa16c49aa82ed64aa9d37adbb","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/9cf9c56aa16c49aa82ed64aa9d37adbb","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,"listed_in":[],"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":"Journal of Automation and Intelligence, Vol 2, Iss 3, Pp 146-151 (2023)","raw_type":"article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/228178","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/228178","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1016/j.jai.2023.08.002","doi":"https://doi.org/10.1016/j.jai.2023.08.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jai.2023.08.002","pdf_url":null,"source":{"id":"https://openalex.org/S4387285287","display_name":"Journal of Automation and Intelligence","issn_l":"2949-8554","issn":["2949-8554"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","oarl"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Automation and Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2158131535","https://openalex.org/W2501692359","https://openalex.org/W2799166040","https://openalex.org/W2809598685","https://openalex.org/W2964137095","https://openalex.org/W3176730699","https://openalex.org/W3196623383","https://openalex.org/W3197503774","https://openalex.org/W3198344283","https://openalex.org/W3204699193","https://openalex.org/W3216799986","https://openalex.org/W4288391511","https://openalex.org/W4315750497"],"related_works":["https://openalex.org/W3176220208","https://openalex.org/W3176730699","https://openalex.org/W4416381397","https://openalex.org/W4316660381","https://openalex.org/W7155200663","https://openalex.org/W2166099681","https://openalex.org/W4410762276","https://openalex.org/W4316660287","https://openalex.org/W3035800218","https://openalex.org/W4391789273"],"abstract_inverted_index":{"This":[0,89],"paper":[1],"presents":[2],"a":[3,94,113,134,154],"novel":[4],"approach":[5],"for":[6,29],"tire-pattern":[7],"classification,":[8],"aimed":[9],"at":[10,18],"conducting":[11],"forensic":[12],"analysis":[13],"on":[14,78,84,195],"tire":[15,36,75,101,151,209],"marks":[16,82,103,108],"discovered":[17],"crime":[19],"scenes.":[20],"The":[21,64,130],"classification":[22,213,219],"model":[23,51,65,97,132,169,191,205],"proposed":[24,131],"in":[25,39,162,185],"this":[26,47],"study":[27],"accounts":[28],"the":[30,49,56,100,105,118,124,138,146,150,159,165,168,179,183,186,190,208,215],"intricate":[31],"and":[32,69,80,121,171],"dynamic":[33],"nature":[34],"of":[35,59,149,182,203,218],"prints":[37],"found":[38],"real-world":[40],"scenarios,":[41],"including":[42],"accident":[43],"sites.":[44],"To":[45],"address":[46],"complexity,":[48],"classifier":[50,125],"was":[52],"developed":[53],"to":[54,71,87,98,126,144,174,206],"harness":[55],"meta-learning":[57],"capabilities":[58],"few-shot":[60],"learning":[61],"algorithms":[62],"(learning-to-learn).":[63],"is":[66,90,142],"meticulously":[67],"designed":[68],"optimized":[70],"effectively":[72],"classify":[73],"both":[74],"patterns":[76,210],"exhibited":[77],"wheels":[79],"tire-indentation":[81],"visible":[83],"surfaces":[85],"due":[86],"friction.":[88],"achieved":[91],"by":[92,220],"employing":[93],"semantic":[95,147,160,204],"segmentation":[96,148],"extract":[99,207],"pattern":[102,152],"within":[104,153],"image.":[106,156],"These":[107],"are":[109],"subsequently":[110],"used":[111],"as":[112],"mask":[114],"channel,":[115],"combined":[116],"with":[117,164],"original":[119,166],"image,":[120,167],"fed":[122],"into":[123],"perform":[127],"classification.":[128],"Overall,":[129],"follows":[133],"three-step":[135],"process:":[136],"(i)":[137],"Bilateral":[139],"Segmentation":[140],"Network":[141],"employed":[143],"derive":[145],"given":[155],"(ii)":[157],"utilizing":[158],"image":[161,184],"conjunction":[163],"learns":[170],"clusters":[172],"groups":[173],"generate":[175],"vectors":[176],"that":[177],"define":[178],"relative":[180],"position":[181],"test":[187],"set.":[188],"(iii)":[189],"performs":[192],"predictions":[193],"based":[194],"these":[196],"learned":[197],"features.":[198],"Empirical":[199],"verification":[200],"demonstrates":[201],"usage":[202],"before":[211],"performing":[212],"increases":[214],"overall":[216],"accuracy":[217],"\u223c4%.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-08-23T00:00:00"}