{"id":"https://openalex.org/W2143103220","doi":"https://doi.org/10.1109/ijcnn.2000.861436","title":"A neural network approach to maximum likelihood estimation for eddy-current back-scattering NDE data inversion","display_name":"A neural network approach to maximum likelihood estimation for eddy-current back-scattering NDE data inversion","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W2143103220","doi":"https://doi.org/10.1109/ijcnn.2000.861436","mag":"2143103220"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2000.861436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2000.861436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium","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/A5079056700","display_name":"Simone Fiori","orcid":"https://orcid.org/0000-0001-5964-7464"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"S. Fiori","raw_affiliation_strings":["Department of Industrial Engineering, University of Perugia, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, University of Perugia, Italy","institution_ids":["https://openalex.org/I27483092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048165504","display_name":"Pietro Burrascano","orcid":"https://orcid.org/0000-0003-4094-7621"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"P. Burrascano","raw_affiliation_strings":["Department of Industrial Engineering, University of Perugia, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, University of Perugia, Italy","institution_ids":["https://openalex.org/I27483092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079056700"],"corresponding_institution_ids":["https://openalex.org/I27483092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25456703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5a","issue":null,"first_page":"65","last_page":"70 vol.5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":1.0,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/inversion","display_name":"Inversion (geology)","score":0.6283049583435059},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6249323487281799},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5907570719718933},{"id":"https://openalex.org/keywords/eddy-current-testing","display_name":"Eddy-current testing","score":0.5579598546028137},{"id":"https://openalex.org/keywords/eddy-current","display_name":"Eddy current","score":0.5532243251800537},{"id":"https://openalex.org/keywords/electrical-impedance","display_name":"Electrical impedance","score":0.53648841381073},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5100139379501343},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.49720218777656555},{"id":"https://openalex.org/keywords/nondestructive-testing","display_name":"Nondestructive testing","score":0.4902980625629425},{"id":"https://openalex.org/keywords/electrical-conductor","display_name":"Electrical conductor","score":0.46276894211769104},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4569346308708191},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4195808470249176},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.35921356081962585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3587246239185333},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21190470457077026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18661141395568848},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1725442111492157},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16579997539520264},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.14888694882392883},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.11561623215675354}],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.6283049583435059},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6249323487281799},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5907570719718933},{"id":"https://openalex.org/C6441794","wikidata":"https://www.wikidata.org/wiki/Q1420867","display_name":"Eddy-current testing","level":3,"score":0.5579598546028137},{"id":"https://openalex.org/C131357438","wikidata":"https://www.wikidata.org/wiki/Q208598","display_name":"Eddy current","level":2,"score":0.5532243251800537},{"id":"https://openalex.org/C17829176","wikidata":"https://www.wikidata.org/wiki/Q179043","display_name":"Electrical impedance","level":2,"score":0.53648841381073},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5100139379501343},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.49720218777656555},{"id":"https://openalex.org/C56529433","wikidata":"https://www.wikidata.org/wiki/Q626700","display_name":"Nondestructive testing","level":2,"score":0.4902980625629425},{"id":"https://openalex.org/C202374169","wikidata":"https://www.wikidata.org/wiki/Q124291","display_name":"Electrical conductor","level":2,"score":0.46276894211769104},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4569346308708191},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4195808470249176},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.35921356081962585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3587246239185333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21190470457077026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18661141395568848},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1725442111492157},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16579997539520264},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.14888694882392883},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.11561623215675354},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2000.861436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2000.861436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.univpm.it:11566/73854","is_oa":false,"landing_page_url":"http://hdl.handle.net/11566/73854","pdf_url":null,"source":{"id":"https://openalex.org/S4306402571","display_name":"Universit\u00e0 Politecnica delle Marche (Universit\u00e0 Politecnica delle Marche)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122534668","host_organization_name":"Marche Polytechnic University","host_organization_lineage":["https://openalex.org/I122534668"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/bookPart"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1554663460","https://openalex.org/W1623007650","https://openalex.org/W1992254999","https://openalex.org/W2055130415","https://openalex.org/W2082285858","https://openalex.org/W2985057205","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W2744634501","https://openalex.org/W2085805524","https://openalex.org/W2003522138","https://openalex.org/W4296871629","https://openalex.org/W2333795440","https://openalex.org/W2369672268","https://openalex.org/W1680801918","https://openalex.org/W2102849516","https://openalex.org/W1972402538","https://openalex.org/W4230069654"],"abstract_inverted_index":{"The":[0],"aim":[1],"of":[2,47,62,79,99,146,159],"this":[3,42,140,151],"paper":[4,141],"is":[5,72,120,124],"to":[6,12,75,128,155],"present":[7],"a":[8,26,45,100,117,131,147],"neural":[9],"network":[10],"approach":[11],"crack":[13],"location":[14,61],"based":[15,91],"on":[16,55,92],"eddy-current":[17],"backscattering":[18],"measured":[19,68],"data":[20,70,84,108],"inversion.":[21],"A":[22],"deep":[23],"defect":[24],"inside":[25],"conductive":[27],"object":[28],"may":[29],"be":[30,129,136,156],"revealed":[31],"by":[32,111],"sliding":[33],"an":[34],"electromagnetic":[35],"probe":[36],"over":[37],"the":[38,57,60,63,67,77,80,89,97,105,107,112,144],"object's":[39],"accessible":[40],"surface:":[41],"operation":[43],"gives":[44],"set":[46],"differential":[48],"impedance":[49,69],"measures,":[50],"whose":[51],"configuration":[52],"carries":[53],"information":[54],"both":[56],"shape":[58],"and":[59,164],"crack.":[64],"By":[65],"inverting":[66],"it":[71],"thus":[73],"possible":[74],"reconstruct":[76],"geometry":[78],"defect.":[81],"Commonly":[82],"employed":[83],"inversion":[85],"techniques,":[86],"such":[87],"as":[88],"one":[90],"maximum":[93],"likelihood":[94],"theory,":[95],"require":[96],"availability":[98],"forward":[101],"model":[102,119,134],"which":[103,153],"describes":[104],"way":[106],"are":[109],"generated":[110],"system":[113,165],"under":[114],"test.":[115],"When":[116],"physical":[118],"not":[121],"available":[122],"or":[123],"too":[125],"much":[126],"difficult":[127],"handled,":[130],"suitable":[132],"black-box":[133],"could":[135],"used":[137],"instead.":[138],"In":[139],"we":[142],"propose":[143],"use":[145],"multilayer":[148],"perceptron":[149],"for":[150],"purpose,":[152],"proved":[154],"effective":[157],"because":[158],"its":[160],"well-known":[161],"function":[162],"approximation":[163],"identification":[166],"capabilities.":[167]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
