{"id":"https://openalex.org/W7126037925","doi":"https://doi.org/10.1109/wpmc67460.2025.11351276","title":"Attention is All Railway Wheels Need in the 21st Century: Revolutionizing Real-Time Defect Detection with NCRA-YOLO","display_name":"Attention is All Railway Wheels Need in the 21st Century: Revolutionizing Real-Time Defect Detection with NCRA-YOLO","publication_year":2025,"publication_date":"2025-11-09","ids":{"openalex":"https://openalex.org/W7126037925","doi":"https://doi.org/10.1109/wpmc67460.2025.11351276"},"language":null,"primary_location":{"id":"doi:10.1109/wpmc67460.2025.11351276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wpmc67460.2025.11351276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Symposium on Wireless Personal Multimedia Communications (WPMC)","raw_type":"proceedings-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/A5074343109","display_name":"Muhammad Zakir Shaikh","orcid":"https://orcid.org/0000-0003-4068-0875"},"institutions":[{"id":"https://openalex.org/I82767444","display_name":"Universidad de M\u00e1laga","ror":"https://ror.org/036b2ww28","country_code":"ES","type":"education","lineage":["https://openalex.org/I82767444"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Muhammad Zakir Shaikh","raw_affiliation_strings":["University of Malaga,Mechanical Engineering and Energy Efficiency, School of Industrial Engineering,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Malaga,Mechanical Engineering and Energy Efficiency, School of Industrial Engineering,Spain","institution_ids":["https://openalex.org/I82767444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121065523","display_name":"Sahil Jatoi","orcid":null},"institutions":[{"id":"https://openalex.org/I180291457","display_name":"Mehran University of Engineering and Technology","ror":"https://ror.org/0575ttm03","country_code":"PK","type":"education","lineage":["https://openalex.org/I180291457"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Sahil Jatoi","raw_affiliation_strings":["Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan","institution_ids":["https://openalex.org/I180291457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046339751","display_name":"Enrique Nava Baro","orcid":"https://orcid.org/0000-0001-7817-6442"},"institutions":[{"id":"https://openalex.org/I82767444","display_name":"Universidad de M\u00e1laga","ror":"https://ror.org/036b2ww28","country_code":"ES","type":"education","lineage":["https://openalex.org/I82767444"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Enrique Nava Baro","raw_affiliation_strings":["Universidad de Malaga,Departamento de Ingenier&#x00ED;a de Comunicaciones,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad de Malaga,Departamento de Ingenier&#x00ED;a de Comunicaciones,Spain","institution_ids":["https://openalex.org/I82767444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124245915","display_name":"Bushra Abro","orcid":null},"institutions":[{"id":"https://openalex.org/I180291457","display_name":"Mehran University of Engineering and Technology","ror":"https://ror.org/0575ttm03","country_code":"PK","type":"education","lineage":["https://openalex.org/I180291457"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Bushra Abro","raw_affiliation_strings":["Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan","institution_ids":["https://openalex.org/I180291457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054696693","display_name":"Agata Manolova","orcid":"https://orcid.org/0000-0002-8120-363X"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Agata Manolova","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034155059","display_name":"Bhawani Shankar Chowdhry","orcid":"https://orcid.org/0000-0002-4340-9602"},"institutions":[{"id":"https://openalex.org/I180291457","display_name":"Mehran University of Engineering and Technology","ror":"https://ror.org/0575ttm03","country_code":"PK","type":"education","lineage":["https://openalex.org/I180291457"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Bhawani Shankar Chowdhry","raw_affiliation_strings":["Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mehran University of Engineering and Technology (MUET),National Centre for Robotics, Automation and Artificial Intelligence,Jamshoro,Pakistan","institution_ids":["https://openalex.org/I180291457"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5074343109"],"corresponding_institution_ids":["https://openalex.org/I82767444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55731302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.8287000060081482,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10842","display_name":"Railway Engineering and Dynamics","score":0.8287000060081482,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.05040000006556511,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.026100000366568565,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/visual-inspection","display_name":"Visual inspection","score":0.4645000100135803},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4083999991416931},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4023999869823456},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.32510000467300415},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3246000111103058}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.535099983215332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4918999969959259},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.4645000100135803},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4194999933242798},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3564999997615814},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.34279999136924744},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.29490000009536743},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2890999913215637},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wpmc67460.2025.11351276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wpmc67460.2025.11351276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Symposium on Wireless Personal Multimedia Communications (WPMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4170187711715698,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310936","display_name":"Ministry of Education and Science","ror":"https://ror.org/03ck0h361"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2013471523","https://openalex.org/W2092363020","https://openalex.org/W2341147505","https://openalex.org/W2461445497","https://openalex.org/W3035750201","https://openalex.org/W3044388823","https://openalex.org/W3184824399","https://openalex.org/W3197445285","https://openalex.org/W4241007795","https://openalex.org/W4312090391","https://openalex.org/W4320002767","https://openalex.org/W4388782010","https://openalex.org/W4396670630","https://openalex.org/W4401049695","https://openalex.org/W4403504095","https://openalex.org/W4405845433","https://openalex.org/W4405846574","https://openalex.org/W4407761660","https://openalex.org/W4407951324","https://openalex.org/W4410216413"],"related_works":[],"abstract_inverted_index":{"The":[0,79,94,132],"safety":[1],"and":[2,16,27,38,84,103,120,139],"operational":[3,36],"efficiency":[4,37],"of":[5,13,34,71,76,99,137,147,152],"railway":[6,14],"infrastructural":[7],"heavily":[8],"relies":[9],"on":[10],"the":[11,111,160],"condition":[12],"wheelsets":[15],"effective":[17,113,162],"defect":[18,51,130],"detection.":[19,131],"Traditional":[20],"inspection":[21,26],"methods":[22],"such":[23],"as":[24,159],"visual":[25],"ultrasonic":[28],"testing":[29,85],"show":[30],"limitations":[31],"in":[32,101,105,127],"terms":[33],"precision,":[35],"scalability.":[39],"In":[40],"this":[41],"study,":[42],"a":[43,135,140],"novel":[44],"approach":[45],"is":[46,110],"presented":[47],"for":[48,82,164],"real-time":[49],"wheelset":[50],"detection":[52],"using":[53],"state-of-the-art":[54],"deep":[55],"learning":[56],"model:":[57],"Neural":[58],"Compact":[59],"Refined":[60],"Architecture-You":[61],"Look":[62],"Only":[63],"Once":[64],"model":[65,95,109,133,163],"(NCRA-YOLO).":[66],"A":[67],"large":[68],"dataset":[69,80],"consists":[70],"7487":[72],"high-resolution":[73],"annotated":[74],"images":[75],"different":[77],"wheelset.":[78],"used":[81],"training":[83],"utilized":[86],"advanced":[87],"data":[88],"augmentation":[89],"techniques":[90],"to":[91,149,166],"enhance":[92],"performance.":[93],"demonstrated":[96],"superior":[97],"accuracy":[98],"100%":[100],"fracture":[102],"83%":[104],"spot":[106],"class.":[107],"This":[108],"most":[112,161],"solution":[114],"with":[115],"only":[116],"1.3":[117],"million":[118],"parameters":[119],"3.8":[121],"GFLOPS":[122],"that":[123],"proves":[124],"its":[125],"effectiveness":[126],"real":[128],"time":[129],"achieved":[134],"precision":[136,143],"94.7%":[138],"mean":[141],"average":[142],"at":[144],"IoU":[145],"thresholds":[146],"50%":[148],"95%":[150],"(mAP50:95)":[151],"96.1%":[153],"during":[154],"cross":[155],"validation,":[156],"making":[157],"it":[158],"generalizing":[165],"unseen":[167],"data.":[168]},"counts_by_year":[],"updated_date":"2026-05-01T08:36:08.643496","created_date":"2026-01-30T00:00:00"}
