{"id":"https://openalex.org/W7128526644","doi":"https://doi.org/10.17977/um018v8i12025p133-144","title":"Feature Engineering and Anchor Optimization for Enhancing Faster R-CNN Detection of Low-Contrast Steel Surface Defects","display_name":"Feature Engineering and Anchor Optimization for Enhancing Faster R-CNN Detection of Low-Contrast Steel Surface Defects","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7128526644","doi":"https://doi.org/10.17977/um018v8i12025p133-144"},"language":"en","primary_location":{"id":"doi:10.17977/um018v8i12025p133-144","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v8i12025p133-144","pdf_url":"https://citeus.um.ac.id/cgi/viewcontent.cgi?article=1128&context=keds","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://citeus.um.ac.id/cgi/viewcontent.cgi?article=1128&context=keds","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125554139","display_name":"Herdianti Darwis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116576","display_name":"Universitas Muslim Indonesia","ror":"https://ror.org/02c0s8023","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210116576"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Herdianti Darwis","raw_affiliation_strings":["Universitas Muslim Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Muslim Indonesia","institution_ids":["https://openalex.org/I4210116576"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088998410","display_name":"Sitti Nurhalimah","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116576","display_name":"Universitas Muslim Indonesia","ror":"https://ror.org/02c0s8023","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210116576"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Sitti Nurhalimah","raw_affiliation_strings":["Universitas Muslim Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Muslim Indonesia","institution_ids":["https://openalex.org/I4210116576"]}]},{"author_position":"last","author":{"id":null,"display_name":"Huzain Azis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116576","display_name":"Universitas Muslim Indonesia","ror":"https://ror.org/02c0s8023","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210116576"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Huzain Azis","raw_affiliation_strings":["Universitas Muslim Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Muslim Indonesia","institution_ids":["https://openalex.org/I4210116576"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5125554139"],"corresponding_institution_ids":["https://openalex.org/I4210116576"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65622122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"1","first_page":"133","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5555999875068665,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5555999875068665,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.3156999945640564,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.015599999576807022,"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/preprocessor","display_name":"Preprocessor","score":0.6589999794960022},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5787000060081482},{"id":"https://openalex.org/keywords/crazing","display_name":"Crazing","score":0.5580999851226807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46779999136924744},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4528000056743622},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4318999946117401},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.3619999885559082},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.36010000109672546}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6589999794960022},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5787000060081482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5622000098228455},{"id":"https://openalex.org/C73125742","wikidata":"https://www.wikidata.org/wiki/Q1139203","display_name":"Crazing","level":3,"score":0.5580999851226807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5565999746322632},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4528000056743622},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3619999885559082},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.36010000109672546},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.32120001316070557},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.30059999227523804},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C88504338","wikidata":"https://www.wikidata.org/wiki/Q1340805","display_name":"Weldability","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C51413319","wikidata":"https://www.wikidata.org/wiki/Q505996","display_name":"Pallet","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.17977/um018v8i12025p133-144","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v8i12025p133-144","pdf_url":"https://citeus.um.ac.id/cgi/viewcontent.cgi?article=1128&context=keds","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.17977/um018v8i12025p133-144","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v8i12025p133-144","pdf_url":"https://citeus.um.ac.id/cgi/viewcontent.cgi?article=1128&context=keds","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6501147150993347,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7128526644.pdf","grobid_xml":"https://content.openalex.org/works/W7128526644.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Detection":[0],"of":[1,36,94,99,112,115,148],"defects":[2],"on":[3],"low-contrast":[4],"steel":[5,183],"surfaces,":[6],"especially":[7],"crazing":[8,102],"and":[9,72,103,122,151],"rolled-in-scale,":[10],"remains":[11],"a":[12,91],"major":[13],"challenge":[14],"due":[15],"to":[16,20,49,56,60,166],"their":[17],"visual":[18],"similarity":[19],"background":[21],"patterns.":[22],"Although":[23,107],"state-of-the-art":[24,116],"methods":[25],"have":[26],"achieved":[27,90],"high":[28],"accuracy":[29],"through":[30],"complex":[31],"architectural":[32,141],"adjustments,":[33],"the":[34,82,113,146,159],"contribution":[35],"preprocessing":[37,131,178],"techniques":[38],"has":[39],"not":[40],"been":[41],"thoroughly":[42],"investigated.":[43],"This":[44,143],"study":[45,144],"investigates":[46],"pre-processing-based":[47],"improvements":[48,132],"Faster":[50,87],"R-CNN":[51,88],"by":[52],"combining":[53],"Bilateral":[54,149],"Filtering":[55,150],"reduce":[57],"noise,":[58],"CLAHE":[59,152],"enhance":[61],"local":[62],"contrast,":[63],"CIoU":[64],"Loss":[65],"for":[66,76,101,105,161,182],"more":[67,162],"effective":[68],"bounding":[69],"box":[70],"regression,":[71],"customized":[73],"anchor":[74],"settings":[75],"irregular":[77],"defect":[78],"configurations.":[79],"Evaluated":[80],"using":[81],"NEU-DET":[83],"dataset,":[84],"our":[85,127],"BF-CIoU":[86],"model":[89],"mAP@50":[92],"score":[93],"72.32%,":[95],"with":[96,179],"an":[97],"AP":[98],"43.74%":[100],"53.04%":[104],"rolled-in-scale.":[106],"these":[108],"results":[109],"fall":[110],"short":[111],"performance":[114,138],"architectures":[117,181],"that":[118,130,176],"utilize":[119],"feature":[120],"fusion":[121],"attention":[123],"mechanisms":[124],"(80.2%":[125],"mAP),":[126],"approach":[128],"demonstrates":[129],"alone":[133],"can":[134],"yield":[135],"competitive":[136],"baseline":[137],"without":[139],"additional":[140],"complexity.":[142],"confirms":[145],"effectiveness":[147],"in":[153,186],"removing":[154],"defective":[155],"signals,":[156],"while":[157],"highlighting":[158],"need":[160],"advanced":[163],"feature-extraction":[164],"modules":[165],"achieve":[167],"higher":[168],"accuracy.":[169],"Further":[170],"research":[171],"will":[172],"examine":[173],"hybrid":[174],"approaches":[175],"combine":[177],"attention-based":[180],"inspection":[184],"systems":[185],"industry.":[187]},"counts_by_year":[],"updated_date":"2026-05-23T06:10:36.450269","created_date":"2026-02-11T00:00:00"}