{"id":"https://openalex.org/W4310722271","doi":"https://doi.org/10.1109/metroxraine54828.2022.9967536","title":"Deep Learning Based Detachment Segmentation: the MIRET Approach","display_name":"Deep Learning Based Detachment Segmentation: the MIRET Approach","publication_year":2022,"publication_date":"2022-10-26","ids":{"openalex":"https://openalex.org/W4310722271","doi":"https://doi.org/10.1109/metroxraine54828.2022.9967536"},"language":"en","primary_location":{"id":"doi:10.1109/metroxraine54828.2022.9967536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroxraine54828.2022.9967536","pdf_url":null,"source":{"id":"https://openalex.org/S4363608343","display_name":"2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)","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/A5012345976","display_name":"Federico Foria","orcid":"https://orcid.org/0000-0002-9570-9201"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Federico Foria","raw_affiliation_strings":["ETS Srl,Roma,Italy","ETS Srl, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETS Srl,Roma,Italy","institution_ids":[]},{"raw_affiliation_string":"ETS Srl, Roma, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079676465","display_name":"Mario Calicchio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mario Calicchio","raw_affiliation_strings":["ETS Srl,Roma,Italy","ETS Srl, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETS Srl,Roma,Italy","institution_ids":[]},{"raw_affiliation_string":"ETS Srl, Roma, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070519394","display_name":"Gabriele Miceli","orcid":"https://orcid.org/0000-0002-8835-094X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gabriele Miceli","raw_affiliation_strings":["ETS Srl,Roma,Italy","ETS Srl, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETS Srl,Roma,Italy","institution_ids":[]},{"raw_affiliation_string":"ETS Srl, Roma, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065582176","display_name":"Aniello Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108823","display_name":"Biomolecular Research Genomics (Italy)","ror":"https://ror.org/022fx7a43","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210108823"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Aniello Xie","raw_affiliation_strings":["RMT Srl,Padova,Italy","RMT Srl, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMT Srl,Padova,Italy","institution_ids":["https://openalex.org/I4210108823"]},{"raw_affiliation_string":"RMT Srl, Padova, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041409110","display_name":"Davide Cuccato","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108823","display_name":"Biomolecular Research Genomics (Italy)","ror":"https://ror.org/022fx7a43","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210108823"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Cuccato","raw_affiliation_strings":["RMT Srl,Padova,Italy","RMT Srl, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMT Srl,Padova,Italy","institution_ids":["https://openalex.org/I4210108823"]},{"raw_affiliation_string":"RMT Srl, Padova, Italy","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063548237","display_name":"Alessandro Allegro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108823","display_name":"Biomolecular Research Genomics (Italy)","ror":"https://ror.org/022fx7a43","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210108823"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Allegro","raw_affiliation_strings":["RMT Srl,Padova,Italy","RMT Srl, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMT Srl,Padova,Italy","institution_ids":["https://openalex.org/I4210108823"]},{"raw_affiliation_string":"RMT Srl, Padova, Italy","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31668208,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs 1611 7004","issue":null,"first_page":"422","last_page":"426"},"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7413107752799988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.678988516330719},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6721146106719971},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6333557963371277},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5615557432174683},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5391132831573486},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5185349583625793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4954334497451782},{"id":"https://openalex.org/keywords/asset-management","display_name":"Asset management","score":0.4794574975967407},{"id":"https://openalex.org/keywords/pillar","display_name":"Pillar","score":0.45583510398864746},{"id":"https://openalex.org/keywords/asset","display_name":"Asset (computer security)","score":0.4358234405517578},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37896645069122314},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.35765430331230164},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.31746453046798706},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2741076648235321},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.11688238382339478}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7413107752799988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678988516330719},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6721146106719971},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6333557963371277},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5615557432174683},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5391132831573486},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5185349583625793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4954334497451782},{"id":"https://openalex.org/C2776517139","wikidata":"https://www.wikidata.org/wiki/Q873442","display_name":"Asset management","level":2,"score":0.4794574975967407},{"id":"https://openalex.org/C105289051","wikidata":"https://www.wikidata.org/wiki/Q1930094","display_name":"Pillar","level":2,"score":0.45583510398864746},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.4358234405517578},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37896645069122314},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.35765430331230164},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31746453046798706},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2741076648235321},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.11688238382339478},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/metroxraine54828.2022.9967536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroxraine54828.2022.9967536","pdf_url":null,"source":{"id":"https://openalex.org/S4363608343","display_name":"2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2058333183","https://openalex.org/W2163605009","https://openalex.org/W2963073614","https://openalex.org/W2980610274","https://openalex.org/W3028392891","https://openalex.org/W3099319035","https://openalex.org/W3207537403","https://openalex.org/W4211047195","https://openalex.org/W6684191040","https://openalex.org/W6729966448","https://openalex.org/W6778231270","https://openalex.org/W6785062762","https://openalex.org/W7055793233"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W1494844823","https://openalex.org/W3009911173","https://openalex.org/W1990141680"],"abstract_inverted_index":{"Among":[0],"infrastructure":[1],"diagnostics,":[2],"the":[3,14,33,41,45,67,74,84,92,103,108,120],"maintenance":[4,19],"of":[5,10,40,55,69,76,87,107,116,122,127],"Transportation":[6,130],"Tunnel":[7],"(TT)":[8],"is":[9,119],"paramount":[11],"importance.":[12],"On":[13,44],"one":[15],"hand,":[16,47],"a":[17,99],"predictive":[18],"process":[20],"would":[21],"allow":[22],"for":[23,32,73,102,110],"safety":[24],"compliance,":[25],"preventive":[26],"corrective":[27],"actions,":[28],"and":[29,53,60,64,98,105],"increased":[30],"lifetime":[31],"asset,":[34],"which":[35],"results":[36],"in":[37,137],"improved":[38],"efficiency":[39],"overall":[42],"infrastructure.":[43],"other":[46],"existing":[48],"methods":[49,72],"to":[50],"perform":[51],"diagnosis":[52],"detection":[54],"these":[56],"anomalies":[57],"are":[58],"inexpensive":[59],"time-consuming.":[61],"Thus,":[62],"ETS":[63,90],"RMT":[65],"foresee":[66],"development":[68],"deep":[70],"learning-based":[71],"segmentation":[75,121],"defects":[77],"on":[78,125],"TT":[79],"images.":[80],"This":[81],"stands":[82],"as":[83],"technological":[85],"pillar":[86],"two":[88],"innovative":[89,93],"projects:":[91],"multi-dimensional":[94],"survey":[95],"system":[96],"(ARCHITA),":[97],"new":[100],"approach":[101],"Management":[104],"Identification":[106],"Risk":[109],"Existing":[111],"Tunnels":[112],"(MIRET).":[113],"The":[114],"focus":[115],"this":[117],"communication":[118],"superficial":[123],"detachments":[124],"data":[126],"concrete":[128],"type":[129],"Tunnels,":[131],"using":[132],"convolutional":[133],"neural":[134],"networks":[135],"trained":[136],"an":[138],"adversarial":[139],"fashion.":[140]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}