{"id":"https://openalex.org/W4415707861","doi":"https://doi.org/10.1109/icme59968.2025.11209168","title":"Relational Enhancement Network for Industrial Defect Detection","display_name":"Relational Enhancement Network for Industrial Defect Detection","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415707861","doi":"https://doi.org/10.1109/icme59968.2025.11209168"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5120192661","display_name":"Haotian Linghu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haotian Linghu","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,National Key Laboratory of Human-Machine Hybrid Augmented Intelligence,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,National Key Laboratory of Human-Machine Hybrid Augmented Intelligence,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033808402","display_name":"Meiqin Liu","orcid":"https://orcid.org/0000-0003-0693-6574"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiqin Liu","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,National Key Laboratory of Human-Machine Hybrid Augmented Intelligence,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,National Key Laboratory of Human-Machine Hybrid Augmented Intelligence,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003643230","display_name":"Senlin Zhang","orcid":"https://orcid.org/0000-0001-5117-3110"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Senlin Zhang","raw_affiliation_strings":["Zhejiang University,College of Electrical Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Electrical Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120192661"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30904622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.40950000286102295,"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":0.40950000286102295,"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":0.383899986743927,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.021900000050663948,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6154999732971191},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5685999989509583},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5533000230789185},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5160999894142151},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.4993000030517578},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.35339999198913574},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.35089999437332153},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3434000015258789}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6708999872207642},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5685999989509583},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5160999894142151},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4993000030517578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48420000076293945},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45190000534057617},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.35089999437332153},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3434000015258789},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3021000027656555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2799215407","https://openalex.org/W2944303778","https://openalex.org/W2948519073","https://openalex.org/W2963037989","https://openalex.org/W2963093690","https://openalex.org/W2963150697","https://openalex.org/W2964080601","https://openalex.org/W3010415660","https://openalex.org/W3046838151","https://openalex.org/W3094019236","https://openalex.org/W3096609285","https://openalex.org/W3138786441","https://openalex.org/W3211328899","https://openalex.org/W4214507171","https://openalex.org/W4361002048","https://openalex.org/W4362575754","https://openalex.org/W4378697379","https://openalex.org/W4382059335","https://openalex.org/W4400381853","https://openalex.org/W4402754006","https://openalex.org/W4402979728","https://openalex.org/W4402979967","https://openalex.org/W4403770406","https://openalex.org/W4403943254"],"related_works":[],"abstract_inverted_index":{"As":[0],"industrial":[1,18,140],"manufacturing":[2],"quality":[3],"standards":[4],"rise,":[5],"demand":[6],"for":[7,62],"advanced":[8],"defect":[9,51,63,67,141,161],"detection":[10,29,156],"models":[11,30],"has":[12],"surged.":[13],"Compared":[14],"to":[15,38,83,97,108,173],"generic":[16],"objects,":[17],"defects":[19,107],"exhibit":[20],"more":[21],"diverse":[22],"and":[23,26,73,100,147,158],"complex":[24,50,104],"shapes":[25],"sizes.":[27],"Traditional":[28],"typically":[31],"process":[32,114],"each":[33],"instance":[34],"in":[35,155],"isolation,":[36],"leading":[37],"incomplete":[39,160],"detections":[40],"(e.g.":[41],"fragmented":[42],"or":[43],"redundant":[44],"bounding":[45],"boxes)":[46],"when":[47],"facing":[48],"such":[49],"patterns.":[52],"To":[53],"address":[54],"these":[55],"challenges,":[56],"we":[57],"propose":[58],"Relational":[59],"Enhancement":[60],"Network":[61],"detection,":[64],"which":[65],"enhances":[66],"features":[68,86],"by":[69],"exploring":[70],"implicit":[71],"spatial":[72,135],"semantic":[74,101],"relations.":[75],"Our":[76],"model":[77],"introduces":[78],"a":[79,88,119],"position":[80],"embedding":[81],"module":[82,94],"map":[84],"geometric":[85,99],"into":[87],"high-dimensional":[89],"space.":[90],"A":[91],"relational":[92,120],"enhancement":[93],"is":[95,115,179],"proposed":[96,124],"integrate":[98],"features,":[102],"capturing":[103],"interactions":[105],"among":[106],"enhance":[109],"the":[110],"original":[111],"features.":[112],"This":[113],"dynamically":[116],"adjusted":[117],"through":[118],"refining":[121],"mechanism.":[122],"The":[123,177],"position-sensitive":[125],"loss":[126],"further":[127],"aligns":[128],"classification":[129],"task":[130,133],"with":[131],"localization":[132],"using":[134],"metrics.":[136],"Experiments":[137],"on":[138],"three":[139],"benchmark":[142],"datasets":[143],"(metals,":[144],"bearings,":[145],"engines,":[146],"LEDs)":[148],"show":[149],"our":[150,164],"method":[151,165],"outperforms":[152],"state-of-the-art":[153],"approaches":[154],"precision":[157],"addresses":[159],"detection.":[162],"Additionally,":[163],"exhibits":[166],"strong":[167],"transferability,":[168],"theoretically":[169],"offering":[170],"clear":[171],"improvements":[172],"any":[174],"similar-structured":[175],"methods.":[176],"code":[178],"available":[180],"at":[181],"https://github.com/lhht/Relational-Enhancement-Network":[182]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-30T00:00:00"}
