{"id":"https://openalex.org/W4408092234","doi":"https://doi.org/10.1109/tim.2025.3547078","title":"CAFS-Net: Context-Aware Feature Selection Network for Accurate and Efficient Tiny Surface Defect Segmentation","display_name":"CAFS-Net: Context-Aware Feature Selection Network for Accurate and Efficient Tiny Surface Defect Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408092234","doi":"https://doi.org/10.1109/tim.2025.3547078"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3547078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3547078","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/A5102818942","display_name":"Zhonghua Tian","orcid":"https://orcid.org/0009-0003-1243-4826"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhonghua Tian","raw_affiliation_strings":["Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014117708","display_name":"Xianqiang Yang","orcid":"https://orcid.org/0000-0002-0036-6921"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianqiang Yang","raw_affiliation_strings":["Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102818942"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":2.5142,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.88222217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"11"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9873999953269958,"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"}},{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9855999946594238,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7461957335472107},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6835578680038452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6447160840034485},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6248664259910583},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6089540719985962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.551538348197937},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.5487580299377441},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5446824431419373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49372848868370056},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4403531551361084},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4107479751110077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1016930639743805},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07568776607513428}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7461957335472107},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6835578680038452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6447160840034485},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6248664259910583},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6089540719985962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.551538348197937},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.5487580299377441},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5446824431419373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49372848868370056},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4403531551361084},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4107479751110077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1016930639743805},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07568776607513428},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3547078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3547078","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":[],"awards":[{"id":"https://openalex.org/G5892101493","display_name":null,"funder_award_id":"HIT.OCEF.2023008","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2752782242","https://openalex.org/W2895340641","https://openalex.org/W2964217532","https://openalex.org/W2965391153","https://openalex.org/W2970055542","https://openalex.org/W2982083293","https://openalex.org/W3012523496","https://openalex.org/W3016719260","https://openalex.org/W3127674103","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3166166117","https://openalex.org/W3170841864","https://openalex.org/W4214694907","https://openalex.org/W4220828048","https://openalex.org/W4224931281","https://openalex.org/W4226212070","https://openalex.org/W4282929256","https://openalex.org/W4285240374","https://openalex.org/W4293094633","https://openalex.org/W4312351417","https://openalex.org/W4312443924","https://openalex.org/W4312815172","https://openalex.org/W4313270795","https://openalex.org/W4367663339","https://openalex.org/W4386071462","https://openalex.org/W4386076267","https://openalex.org/W4388505032","https://openalex.org/W4390874124","https://openalex.org/W6739901393","https://openalex.org/W6760613829","https://openalex.org/W6789654255","https://openalex.org/W6797399245","https://openalex.org/W6810597838","https://openalex.org/W6842806116"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W338149487","https://openalex.org/W4403012196","https://openalex.org/W2972032537","https://openalex.org/W150363521","https://openalex.org/W3154107650","https://openalex.org/W2613671004"],"abstract_inverted_index":{"Although":[0],"deep":[1],"learning-based":[2],"methods":[3,28,250],"have":[4],"achieved":[5],"remarkable":[6],"performance":[7,235],"in":[8,17,251],"the":[9,26,118,146,154,158,165,176,180,196,212,221,231],"industrial":[10],"defect":[11,15,39,208,217,226],"segmentation":[12,16,177,209,218,227],"area,":[13],"tiny":[14,38,122],"ultrahigh-resolution":[18],"image":[19,143,150,182],"scenarios":[20],"still":[21],"remains":[22],"unexplored.":[23],"Most":[24],"of":[25,61,79,142,149,179,236],"existing":[27],"utilize":[29],"attention":[30],"mechanisms":[31],"and":[32,91,104,112,124,135,174,220,233,254],"a":[33,59,71,80,85,92,130,136,187],"sliding":[34],"window":[35],"strategy":[36,193],"for":[37,138],"segmentation.":[40],"However,":[41],"this":[42,67],"approach":[43],"is":[44,98],"not":[45],"only":[46],"computationally":[47],"demanding":[48],"but":[49],"also":[50],"prone":[51],"to":[52,108,164,169,194,229],"texture":[53,125],"noise":[54],"interference,":[55],"likely":[56],"stemming":[57],"from":[58,145],"lack":[60],"global":[62,113],"contextual":[63],"understanding.":[64],"To":[65],"alleviate":[66],"challenge,":[68],"we":[69,185],"propose":[70,186],"context-aware":[72,81],"feature":[73,87,147,172],"selection":[74,88],"network":[75,83],"(CAFS-Net)":[76],"which":[77],"consists":[78],"encoder":[82],"(CANet),":[84],"novel":[86],"module":[89,215],"(FSM),":[90],"lightweight":[93,166],"feature-fusing":[94,167],"decoder.":[95],"The":[96,127,240],"CANet":[97],"constructed":[99],"by":[100],"low-level":[101],"convolutional":[102],"blocks":[103,107,144,151],"high-level":[105],"transformer":[106],"capture":[109],"both":[110,252],"local":[111],"context":[114],"information,":[115],"thereby":[116],"enhancing":[117],"discrimination":[119],"ability":[120],"between":[121],"defects":[123],"noise.":[126],"FSM":[128],"includes":[129],"multilayer":[131],"perceptron":[132],"(MLP)":[133],"classifier":[134],"selector":[137],"selecting":[139],"defective":[140,160,181],"features":[141,161],"pyramid":[148],"based":[152],"on":[153,206],"classification":[155],"outcomes.":[156],"Then,":[157],"selected":[159],"are":[162],"fed":[163],"decoder":[168],"perform":[170],"multiscale":[171],"fusion":[173],"obtain":[175],"masks":[178],"patches.":[183],"Additionally,":[184],"concentrated":[188],"random":[189],"cropping":[190],"data":[191],"augmentation":[192],"address":[195],"class":[197],"imbalance":[198],"problem":[199],"during":[200],"training.":[201],"We":[202],"conducted":[203],"extensive":[204],"experiments":[205],"two":[207],"datasets,":[210],"including":[211],"compact":[213],"camera":[214],"(CCM)":[216],"dataset":[219],"printed":[222],"circuit":[223],"board":[224],"(PCB)":[225],"dataset,":[228],"demonstrate":[230],"superiority":[232],"generalization":[234],"our":[237,244],"proposed":[238],"model.":[239],"results":[241],"show":[242],"that":[243],"CAFS-Net":[245],"outperforms":[246],"other":[247],"state-of-the-art":[248],"(SOTA)":[249],"accuracy":[253],"efficiency.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}