{"id":"https://openalex.org/W4372283421","doi":"https://doi.org/10.3233/jifs-230170","title":"An adaptive weighting multimodal fusion classification system for steel plate surface defect","display_name":"An adaptive weighting multimodal fusion classification system for steel plate surface defect","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372283421","doi":"https://doi.org/10.3233/jifs-230170"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-230170","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230170","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","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/A5109604620","display_name":"Feng Miao Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Miao Tu","raw_affiliation_strings":["School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112911743","display_name":"Ming Hui Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Hui Wei","raw_affiliation_strings":["School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003751305","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0001-7367-5824"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["School of Geography and Planning, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112911744","display_name":"Lu Lu Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I106994412","display_name":"Sinopec (China)","ror":"https://ror.org/0161q6d74","country_code":"CN","type":"company","lineage":["https://openalex.org/I106994412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Lu Liao","raw_affiliation_strings":["SINOPEC Research Institute of Petroleum Engineering Co., Ltd, Beijing, China","E-mail:"],"affiliations":[{"raw_affiliation_string":"SINOPEC Research Institute of Petroleum Engineering Co., Ltd, Beijing, China","institution_ids":["https://openalex.org/I106994412"]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112911743"],"corresponding_institution_ids":["https://openalex.org/I165745306"],"apc_list":null,"apc_paid":null,"fwci":0.3087,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52187508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"45","issue":"2","first_page":"3501","last_page":"3512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998000264167786,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9889000058174133,"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/weighting","display_name":"Weighting","score":0.8367946147918701},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7495975494384766},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7149406671524048},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6863107085227966},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6856775879859924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6703088283538818},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6397475004196167},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6394192576408386},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.48516517877578735},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41261428594589233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11328890919685364}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.8367946147918701},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7495975494384766},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149406671524048},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6863107085227966},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6856775879859924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6703088283538818},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6397475004196167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6394192576408386},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.48516517877578735},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41261428594589233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11328890919685364},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-230170","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230170","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W21721183","https://openalex.org/W2058664765","https://openalex.org/W2092072518","https://openalex.org/W2135460975","https://openalex.org/W2163605009","https://openalex.org/W2515602771","https://openalex.org/W2522485430","https://openalex.org/W2763152181","https://openalex.org/W2793828580","https://openalex.org/W2884697329","https://openalex.org/W2899242765","https://openalex.org/W2912069721","https://openalex.org/W2944303778","https://openalex.org/W2952171653","https://openalex.org/W2963838685","https://openalex.org/W2982039661","https://openalex.org/W3048817311","https://openalex.org/W3081383838","https://openalex.org/W3094190573","https://openalex.org/W3100487172","https://openalex.org/W3117733199","https://openalex.org/W3127989846","https://openalex.org/W3138025798","https://openalex.org/W3153037112","https://openalex.org/W3155620069","https://openalex.org/W3159246248","https://openalex.org/W3207184779","https://openalex.org/W3211304631","https://openalex.org/W6684191040","https://openalex.org/W6791907765"],"related_works":["https://openalex.org/W18669731","https://openalex.org/W2383096489","https://openalex.org/W2319888919","https://openalex.org/W2767651786","https://openalex.org/W2912288872","https://openalex.org/W3106036237","https://openalex.org/W3036234374","https://openalex.org/W2402952899","https://openalex.org/W2132592511","https://openalex.org/W2886673456"],"abstract_inverted_index":{"In":[0],"steel":[1,6,114,127],"surface":[2,7,115,129],"inspection,":[3],"an":[4,93],"accurate":[5],"defect":[8,130],"identification":[9],"method":[10],"is":[11,35,159,175],"needed":[12],"to":[13,65,108],"evaluate":[14],"the":[15,26,38,55,79,87,125,133,152,156,171,179,182],"impact":[16],"of":[17,29,77,136,155,181],"defects":[18,116],"on":[19,32,124],"structural":[20],"performance":[21,40],"and":[22,70,82,111,140,145,170],"system":[23,39,101,158],"maintenance.":[24],"Traditionally,":[25],"recognition":[27],"accuracy":[28,154,173],"methods":[30],"based":[31],"handcrafted":[33,83,103],"features":[34,81,104],"limited,":[36],"but":[37],"can":[41],"be":[42],"improved":[43,160],"by":[44,48,161],"feature":[45,84,120,137],"fusion":[46,76,97,142,157],"extracted":[47],"different":[49,119],"methods.":[50],"Therefore,":[51],"this":[52],"research":[53],"uses":[54,102],"pre-trained":[56],"convolutional":[57],"neural":[58],"network":[59],"(CNN)":[60],"combined":[61],"with":[62,166],"transfer":[63],"learning":[64],"extract":[66],"effective":[67],"abstract":[68,80,109],"features,":[69,110],"carries":[71],"out":[72],"adaptive":[73,94],"weighting":[74,95],"multimodal":[75,96],"three":[78],"sets":[85,138],"at":[86,162],"decision-making":[88],"level,":[89],"that":[90,151,167],"is,":[91],"proposes":[92],"classification":[98,134,153],"system.":[99,184],"The":[100,147],"as":[105],"a":[106],"supplement":[107],"accurately":[112],"classifies":[113],"in":[117],"completely":[118],"representation":[121],"spaces.":[122],"Based":[123],"NEU":[126],"plate":[128],"benchmark":[131],"database,":[132],"results":[135,149],"before":[139,168],"after":[141],"are":[143],"compared":[144,165],"analyzed.":[146],"experimental":[148],"show":[150],"least":[163],"3.4%":[164],"fusion,":[169],"final":[172],"rate":[174],"99.0%,":[176],"which":[177],"proves":[178],"effectiveness":[180],"proposed":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}