{"id":"https://openalex.org/W4206947990","doi":"https://doi.org/10.3390/s22030817","title":"Online Detection of Surface Defects Based on Improved YOLOV3","display_name":"Online Detection of Surface Defects Based on Improved YOLOV3","publication_year":2022,"publication_date":"2022-01-21","ids":{"openalex":"https://openalex.org/W4206947990","doi":"https://doi.org/10.3390/s22030817","pmid":"https://pubmed.ncbi.nlm.nih.gov/35161562"},"language":"en","primary_location":{"id":"doi:10.3390/s22030817","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030817","pdf_url":"https://www.mdpi.com/1424-8220/22/3/817/pdf?version=1643004561","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/3/817/pdf?version=1643004561","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073168673","display_name":"Xuechun Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuechun Chen","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106407118","display_name":"Jun Lv","orcid":"https://orcid.org/0000-0002-0920-8444"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Lv","raw_affiliation_strings":["Faculty of Economics and Management, East China Normal University, Shanghai 200240, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Economics and Management, East China Normal University, Shanghai 200240, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021747394","display_name":"Yulun Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulun Fang","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054008223","display_name":"Shichang Du","orcid":"https://orcid.org/0000-0003-2408-722X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shichang Du","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054008223"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":7.9991,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.97761272,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"22","issue":"3","first_page":"817","last_page":"817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9951000213623047,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9868000149726868,"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":0.6954745650291443},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.66495281457901},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6644924879074097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5423747301101685},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.5058647990226746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49654799699783325},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.48638537526130676},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.447429895401001},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.43577373027801514},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4182107150554657},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3399829864501953},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.13753360509872437},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1005258560180664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6954745650291443},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.66495281457901},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6644924879074097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5423747301101685},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5058647990226746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49654799699783325},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.48638537526130676},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.447429895401001},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.43577373027801514},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4182107150554657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3399829864501953},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.13753360509872437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1005258560180664},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s22030817","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030817","pdf_url":"https://www.mdpi.com/1424-8220/22/3/817/pdf?version=1643004561","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35161562","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35161562","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:c657c0c689a3429bb5e60f213d07f19a","is_oa":true,"landing_page_url":"https://doaj.org/article/c657c0c689a3429bb5e60f213d07f19a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 3, p 817 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/3/817/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22030817","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 3; Pages: 817","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8838028","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8838028","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22030817","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030817","pdf_url":"https://www.mdpi.com/1424-8220/22/3/817/pdf?version=1643004561","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2710222259","display_name":null,"funder_award_id":"51775343","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5167091242","display_name":null,"funder_award_id":"No. 1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206947990.pdf","grobid_xml":"https://content.openalex.org/works/W4206947990.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W2476548250","https://openalex.org/W2565639579","https://openalex.org/W2768955070","https://openalex.org/W2792249564","https://openalex.org/W2884585870","https://openalex.org/W2889035772","https://openalex.org/W2919046835","https://openalex.org/W2919115771","https://openalex.org/W2944303778","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963351448","https://openalex.org/W2982512126","https://openalex.org/W2983363363","https://openalex.org/W3014595575","https://openalex.org/W3034186755","https://openalex.org/W3108566774","https://openalex.org/W3117733199","https://openalex.org/W3129420947","https://openalex.org/W3132963652","https://openalex.org/W3174027023","https://openalex.org/W6786861424"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4249847449","https://openalex.org/W44395729","https://openalex.org/W2611989081","https://openalex.org/W2949096641","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W4254103348","https://openalex.org/W3210378990","https://openalex.org/W3034745255"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,11,37,41,59,76,97,115],"problems":[3],"of":[4,127,163,183],"low":[5],"efficiency":[6],"and":[7,66,82,101,112,139,154,156,170,176,180],"poor":[8],"accuracy":[9],"in":[10,75],"product":[12,184],"surface":[13,21,185],"defect":[14],"detection.":[15],"In":[16,87],"this":[17],"paper,":[18],"an":[19,51,91],"online":[20],"defects":[22,126],"detection":[23,60,65],"method":[24,107,147],"based":[25],"on":[26,114],"YOLOV3":[27],"is":[28,108,167],"proposed.":[29],"Firstly,":[30],"using":[31],"lightweight":[32],"network":[33,46,55],"MobileNetV2":[34],"to":[35,44,57,79,95,110],"replace":[36],"original":[38],"backbone":[39],"as":[40],"feature":[42,53,70],"extractor":[43],"improve":[45],"speed.":[47],"Then,":[48],"we":[49,89],"propose":[50],"extended":[52],"pyramid":[54],"(EFPN)":[56],"extend":[58,77],"layer":[61,78],"for":[62],"multi-size":[63],"object":[64],"design":[67],"a":[68,128,149,161],"novel":[69],"fusing":[71],"module":[72],"(FFM)":[73],"embedded":[74],"super-resolve":[80],"features":[81],"capture":[83],"more":[84,168],"regional":[85],"details.":[86],"addition,":[88],"add":[90],"IoU":[92],"loss":[93],"function":[94],"solve":[96],"mismatch":[98],"between":[99,152],"classification":[100],"bounding":[102],"box":[103],"regression.":[104],"The":[105,141],"proposed":[106],"used":[109],"train":[111],"test":[113],"hot":[116],"rolled":[117],"steel":[118,129],"open":[119],"dataset":[120],"NEU-DET,":[121],"which":[122,166],"contains":[123],"six":[124],"typical":[125],"surface,":[130,137],"namely":[131],"rolled-in":[132],"scale,":[133],"patches,":[134],"crazing,":[135],"pitted":[136],"inclusion":[138],"scratches.":[140],"experimental":[142],"results":[143],"show":[144],"that":[145],"our":[146],"achieves":[148],"satisfactory":[150],"balance":[151],"performance":[153],"consumption":[155],"reaches":[157],"86.96%":[158],"mAP":[159],"with":[160],"speed":[162],"80.96":[164],"FPS,":[165],"accurate":[169],"faster":[171],"than":[172],"many":[173],"other":[174],"algorithms":[175],"can":[177],"realize":[178],"real-time":[179],"high-precision":[181],"inspection":[182],"defects.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":11}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}