{"id":"https://openalex.org/W4312994264","doi":"https://doi.org/10.1109/access.2022.3224594","title":"Detection of Surface Defects on Railway Tracks Based on Deep Learning","display_name":"Detection of Surface Defects on Railway Tracks Based on Deep Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312994264","doi":"https://doi.org/10.1109/access.2022.3224594"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3224594","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224594","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09963529.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09963529.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031904848","display_name":"Maoli Wang","orcid":"https://orcid.org/0000-0001-5420-1463"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoli Wang","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0001-5420-1463","affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060008136","display_name":"Kaizhi Li","orcid":"https://orcid.org/0000-0003-1240-9287"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaizhi Li","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0003-1240-9287","affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005421560","display_name":"Xiao Fang Zhu","orcid":"https://orcid.org/0000-0003-2052-2212"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Zhu","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013369066","display_name":"Yining Zhao","orcid":"https://orcid.org/0000-0002-8518-6152"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yining Zhao","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-8518-6152","affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I202126657"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.6785,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.90822868,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"126451","last_page":"126465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9986000061035156,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/computer-science","display_name":"Computer science","score":0.6938146352767944},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6619853973388672},{"id":"https://openalex.org/keywords/sharpening","display_name":"Sharpening","score":0.6532876491546631},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5531561970710754},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5510870218276978},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5360133647918701},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5334195494651794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47867351770401},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4547017514705658},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4250972867012024},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42470628023147583},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.42060887813568115},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.41905301809310913},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39995720982551575},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.16952961683273315},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08798635005950928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08097031712532043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938146352767944},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6619853973388672},{"id":"https://openalex.org/C2781137444","wikidata":"https://www.wikidata.org/wiki/Q237105","display_name":"Sharpening","level":2,"score":0.6532876491546631},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5531561970710754},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5510870218276978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5360133647918701},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5334195494651794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47867351770401},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4547017514705658},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4250972867012024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42470628023147583},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.42060887813568115},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.41905301809310913},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39995720982551575},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.16952961683273315},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08798635005950928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08097031712532043},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3224594","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224594","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09963529.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fadd1fd3c14849e8a8e8ec48a796215a","is_oa":true,"landing_page_url":"https://doaj.org/article/fadd1fd3c14849e8a8e8ec48a796215a","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":"IEEE Access, Vol 10, Pp 126451-126465 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3224594","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224594","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09963529.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G4727790432","display_name":null,"funder_award_id":"ZR20111260301","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G5630673787","display_name":null,"funder_award_id":"SD2019NJ007","funder_id":"https://openalex.org/F4320326702","funder_display_name":"Shandong Provincial Department of Agriculture and Rural Affairs"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320326702","display_name":"Shandong Provincial Department of Agriculture and Rural Affairs","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312994264.pdf","grobid_xml":"https://content.openalex.org/works/W4312994264.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2752782242","https://openalex.org/W2761216034","https://openalex.org/W2790914279","https://openalex.org/W2803930526","https://openalex.org/W2811331998","https://openalex.org/W2884585870","https://openalex.org/W2900458319","https://openalex.org/W2913074553","https://openalex.org/W2945270739","https://openalex.org/W2955058313","https://openalex.org/W2964093967","https://openalex.org/W2979744596","https://openalex.org/W2991089415","https://openalex.org/W3009013436","https://openalex.org/W3013695998","https://openalex.org/W3018757597","https://openalex.org/W3031070092","https://openalex.org/W3034552520","https://openalex.org/W3037921770","https://openalex.org/W3093994526","https://openalex.org/W3106250896","https://openalex.org/W3110092301","https://openalex.org/W3112721793","https://openalex.org/W3113270537","https://openalex.org/W3128847319","https://openalex.org/W3132135025","https://openalex.org/W3146366485","https://openalex.org/W3152020713","https://openalex.org/W3152382703","https://openalex.org/W3163945827","https://openalex.org/W3169897425","https://openalex.org/W3171297660","https://openalex.org/W3179632985","https://openalex.org/W3195462390","https://openalex.org/W3208486706","https://openalex.org/W3212386989","https://openalex.org/W4200128618","https://openalex.org/W4211177542","https://openalex.org/W4220801936","https://openalex.org/W4225120396","https://openalex.org/W4283032729","https://openalex.org/W4284977113","https://openalex.org/W4291415528","https://openalex.org/W4292672153","https://openalex.org/W4293584584","https://openalex.org/W4296281486","https://openalex.org/W4312243195","https://openalex.org/W4312610334","https://openalex.org/W6750227808","https://openalex.org/W6753412334","https://openalex.org/W6771062828","https://openalex.org/W6777046832","https://openalex.org/W6785652829","https://openalex.org/W6787710438","https://openalex.org/W6793948564"],"related_works":["https://openalex.org/W2329932281","https://openalex.org/W64535957","https://openalex.org/W2043790407","https://openalex.org/W2348902545","https://openalex.org/W2321247741","https://openalex.org/W2136313643","https://openalex.org/W2087564795","https://openalex.org/W2011367085","https://openalex.org/W3136545447","https://openalex.org/W3107835849"],"abstract_inverted_index":{"The":[0,260],"detection":[1,36,56,138,254,272,276,282],"of":[2,19,29,37,99,101,132,140,167,171,184,191,194,219,228,242,278,284],"rail":[3,21,38,53,231,244,269],"surface":[4,39,54,232,270],"defects":[5,15,30,131,249],"is":[6,121,201,237],"very":[7],"important":[8],"in":[9,178],"railway":[10,133],"transportation.":[11],"However,":[12],"the":[13,20,23,35,45,97,102,125,128,137,141,165,168,175,182,188,192,195,197,212,217,226,240,267],"edge":[14,129,144],"on":[16,143,239],"both":[17,31],"sides":[18],"and":[22,77,135,187,246,256,280],"multi-scale":[24],"variation":[25],"between":[26],"different":[27,222],"types":[28],"pose":[32],"challenges":[33],"to":[34,43,123,127,163,180,250],"defects.":[40,145,173],"In":[41,82,109],"order":[42,179],"solve":[44],"above":[46],"problems,":[47],"this":[48,235],"paper":[49,236],"proposes":[50],"a":[51,62,113,149,158,275,281],"novel":[52],"defect":[55,233,271],"network,":[57],"YOLOv5s-VF.":[58],"First,":[59],"we":[60,84,111,147],"design":[61,112],"sharpening":[63,114],"functional":[64],"attention":[65,75,80,103,126],"mechanism":[66,104],"(V-CBAM)":[67],"that":[68,264],"contains":[69],"two":[70],"key":[71],"components:":[72],"adaptive":[73,89,151,205],"channel":[74],"(F-CAM)":[76],"sharpened":[78],"spatial":[79,118,152,206],"(SSA).":[81],"F-CAM,":[83],"use":[85],"one-dimensional":[86],"convolution":[87,90],"with":[88,204,274],"kernels":[91],"for":[92,117],"cross-channel":[93],"connections,":[94],"which":[95,120,156],"reduces":[96],"number":[98],"parameters":[100,193],"without":[105],"affecting":[106],"its":[107],"performance.":[108],"SSA,":[110],"filter":[115],"suitable":[116],"attention,":[119],"used":[122],"enhance":[124,136,164],"position":[130],"tracks":[134],"effect":[139],"network":[142,255],"Second,":[146],"construct":[148],"microscale":[150],"feature":[153,160,199,207],"fusion":[154,218],"(M-ASFF),":[155],"adds":[157],"high-resolution":[159],"extraction":[161],"layer":[162,200],"details":[166],"underlying":[169],"features":[170,220],"tiny":[172],"At":[174],"same":[176],"time,":[177],"prevent":[181,211],"loss":[183],"detailed":[185],"information":[186],"excessive":[189],"increase":[190],"model,":[196],"low-resolution":[198],"removed.":[202],"Combined":[203],"fusion,":[208],"it":[209],"can":[210],"semantic":[213],"conflict":[214],"caused":[215],"by":[216],"at":[221],"scales.":[223],"Finally,":[224],"given":[225],"lack":[227],"labeled":[229],"public":[230],"datasets,":[234],"based":[238],"collection":[241],"real":[243],"images":[245],"manually":[247],"labels":[248],"train":[251],"an":[252],"object":[253],"open":[257],"source":[258],"it.":[259],"experimental":[261],"results":[262],"show":[263],"YOLOv5s-VF":[265],"outperforms":[266],"existing":[268],"methods":[273],"accuracy":[277],"93.5%":[279],"speed":[283],"114.9":[285],"fps.":[286]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}