{"id":"https://openalex.org/W4386212377","doi":"https://doi.org/10.1109/tim.2023.3309374","title":"Global Context-Based Self-Similarity Feature Augmentation and Bidirectional Feature Fusion for Surface Defect Detection","display_name":"Global Context-Based Self-Similarity Feature Augmentation and Bidirectional Feature Fusion for Surface Defect Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386212377","doi":"https://doi.org/10.1109/tim.2023.3309374"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3309374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3309374","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5102820328","display_name":"Hao Wang","orcid":"https://orcid.org/0009-0006-9714-0502"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Wang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0006-9714-0502","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027989162","display_name":"Ruifan Zhang","orcid":"https://orcid.org/0009-0003-2789-4315"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruifan Zhang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0003-2789-4315","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022193251","display_name":"M.Q. Feng","orcid":"https://orcid.org/0009-0009-5573-9586"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyao Feng","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0009-5573-9586","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048223720","display_name":"Yikun Liu","orcid":"https://orcid.org/0000-0001-5698-7623"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yikun Liu","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0001-5698-7623","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036183903","display_name":"Gongping Yang","orcid":"https://orcid.org/0000-0001-7637-2749"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongping Yang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0001-7637-2749","affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102820328"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":2.1729,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88560896,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"12"},"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9883000254631042,"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":0.9825000166893005,"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/context","display_name":"Context (archaeology)","score":0.7042888402938843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.671479344367981},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6713049411773682},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6395421624183655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.564373254776001},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5604981780052185},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4879405200481415},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4619477391242981},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4554469585418701},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.45379436016082764},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44672760367393494},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3315250277519226},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20409080386161804},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18746846914291382},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17900621891021729}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7042888402938843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.671479344367981},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6713049411773682},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6395421624183655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.564373254776001},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5604981780052185},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4879405200481415},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4619477391242981},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4554469585418701},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.45379436016082764},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44672760367393494},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3315250277519226},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20409080386161804},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18746846914291382},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17900621891021729},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3309374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3309374","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G4076825138","display_name":null,"funder_award_id":"62176139","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5634033710","display_name":null,"funder_award_id":"ZR2021ZD15","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W984811894","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1942214758","https://openalex.org/W2018055769","https://openalex.org/W2065178107","https://openalex.org/W2194775991","https://openalex.org/W2318731621","https://openalex.org/W2412782625","https://openalex.org/W2511065100","https://openalex.org/W2516145989","https://openalex.org/W2560023338","https://openalex.org/W2592939477","https://openalex.org/W2601564443","https://openalex.org/W2825063406","https://openalex.org/W2888407265","https://openalex.org/W2895572611","https://openalex.org/W2900618894","https://openalex.org/W2907223224","https://openalex.org/W2907868778","https://openalex.org/W2935842115","https://openalex.org/W2941001797","https://openalex.org/W2944303778","https://openalex.org/W2953868242","https://openalex.org/W2963299740","https://openalex.org/W2963881378","https://openalex.org/W2964308596","https://openalex.org/W2969247748","https://openalex.org/W2980098587","https://openalex.org/W2994615081","https://openalex.org/W3000247513","https://openalex.org/W3035487542","https://openalex.org/W3043497578","https://openalex.org/W3113270537","https://openalex.org/W3124459155","https://openalex.org/W3132936317","https://openalex.org/W3153381206","https://openalex.org/W3173370190","https://openalex.org/W3190335749","https://openalex.org/W4206670089","https://openalex.org/W4293406525","https://openalex.org/W4312702757","https://openalex.org/W4393805319","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6717372056"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W3000105423","https://openalex.org/W2350688482","https://openalex.org/W2122135111","https://openalex.org/W2053575972"],"abstract_inverted_index":{"Surface":[0],"defect":[1,26,107,166,193],"detection":[2,27,44,130],"is":[3,11,137,211],"a":[4,75,83,89],"significant":[5],"step":[6],"in":[7,52,172],"industrial":[8,19],"production,":[9],"which":[10,126],"also":[12],"essential":[13],"for":[14,132,149],"ensuring":[15],"the":[16,22,25,43,47,70,101,106,111,129,141,150,173,176,185,198,208],"quality":[17],"of":[18,49,82,144,153,204,219,223,227,231],"products.":[20],"At":[21,175],"moment,":[23],"although":[24],"methods":[28,216],"based":[29],"on":[30,207],"computer":[31],"vision":[32],"have":[33],"made":[34],"great":[35],"progress,":[36],"they":[37],"are":[38],"still":[39],"tough":[40],"to":[41,46,139,164,213],"automate":[42],"due":[45],"challenges":[48],"large":[50,59],"changes":[51],"size,":[53],"low":[54],"contrast,":[55],"strong":[56],"background":[57,117],"interference,":[58],"intraclass":[60],"difference":[61,113],"as":[62,64],"well":[63],"small":[65],"interclass":[66],"difference.":[67],"To":[68],"address":[69],"above":[71],"issues,":[72],"we":[73,157],"design":[74,158],"deep":[76],"learning":[77],"model":[78],"that":[79,197],"mainly":[80],"consists":[81],"feature":[84,92,112],"augmentation":[85],"module":[86,94],"(FAM),":[87],"and":[88,109,116,123,146,182,191],"multiscale":[90],"bidirectional":[91,142],"fusion":[93,143],"(MBFFM),":[95],"while":[96],"introducing":[97],"deformable":[98,183],"convolutions":[99],"into":[100],"backbone.":[102],"The":[103,135],"FAM":[104],"enhances":[105],"features":[108,148],"magnifies":[110],"between":[114],"defects":[115],"by":[118,168,179],"combining":[119,180],"global":[120],"context-based":[121],"self-similarity":[122],"spatial":[124],"attention,":[125],"can":[127,187],"improve":[128],"performance":[131],"weak":[133],"defects.":[134,154],"MBFFM":[136],"applied":[138],"complete":[140,192],"high-level":[145],"low-level":[147],"overall":[151],"perception":[152],"In":[155],"addition,":[156],"an":[159],"edge":[160],"weight":[161],"loss":[162],"(EWL)":[163],"emphasize":[165],"regions":[167],"increasing":[169],"their":[170],"weights":[171],"loss.":[174],"same":[177],"time,":[178],"EWL":[181],"convolution,":[184],"backbone":[186],"accurately":[188],"extract":[189],"comprehensive":[190],"features.":[194],"Experiments":[195],"verify":[196],"mean":[199],"Intersection":[200],"over":[201],"Union":[202],"(mIoU)":[203],"our":[205],"method":[206],"four":[209],"datasets":[210],"superior":[212],"other":[214],"state-of-the-art":[215],"(MT,":[217],"miou":[218,222,226,230],"83.75%;":[220],"NEU_SEG,":[221],"88.84%;":[224],"DAGM_defect,":[225],"86.74%;":[228],"ROAD,":[229],"76.71%).":[232]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}