{"id":"https://openalex.org/W4401210324","doi":"https://doi.org/10.1109/access.2024.3436681","title":"Comparative Evaluation of Deep Neural Network Performance for Point Cloud-Based IFC Object Classification","display_name":"Comparative Evaluation of Deep Neural Network Performance for Point Cloud-Based IFC Object Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401210324","doi":"https://doi.org/10.1109/access.2024.3436681"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3436681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436681","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3436681","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024384139","display_name":"Majid Seydgar","orcid":"https://orcid.org/0000-0002-0394-5259"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Majid Seydgar","raw_affiliation_strings":["Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-0394-5259","affiliations":[{"raw_affiliation_string":"Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106215472","display_name":"\u00c9rik A. Poirier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u00c9rik A. Poirier","raw_affiliation_strings":["Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025718018","display_name":"Ali Motamedi","orcid":"https://orcid.org/0000-0002-7012-440X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ali Motamedi","raw_affiliation_strings":["Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7012-440X","affiliations":[{"raw_affiliation_string":"Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7284,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77438751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"12","issue":null,"first_page":"108303","last_page":"108312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11006","display_name":"BIM and Construction Integration","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.8093181848526001},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.621497392654419},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5882344245910645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5820208191871643},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5687306523323059},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5682150721549988},{"id":"https://openalex.org/keywords/interoperability","display_name":"Interoperability","score":0.5659065246582031},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5505082607269287},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5293722152709961},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4781975746154785},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.43636471033096313},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4315161108970642},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.421405553817749},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3871919512748718},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1047322154045105},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.0934649407863617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8093181848526001},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.621497392654419},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5882344245910645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5820208191871643},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5687306523323059},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5682150721549988},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.5659065246582031},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5505082607269287},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5293722152709961},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4781975746154785},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.43636471033096313},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4315161108970642},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.421405553817749},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3871919512748718},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1047322154045105},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0934649407863617},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2024.3436681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436681","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:espace2.etsmtl.ca:29375","is_oa":true,"landing_page_url":null,"pdf_url":"https://espace2.etsmtl.ca/id/eprint/29375/1/Poirier-E-2024-29375.pdf","source":{"id":"https://openalex.org/S4306402392","display_name":"Espace \u00c9TS (ETS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1341030882","host_organization_name":"Educational Testing Service","host_organization_lineage":["https://openalex.org/I1341030882"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article publi\u00e9 dans une revue, r\u00e9vis\u00e9 par les pairs"},{"id":"pmh:oai:doaj.org/article:a406e8cebe6d4b988531c9cb4e66ec3f","is_oa":true,"landing_page_url":"https://doaj.org/article/a406e8cebe6d4b988531c9cb4e66ec3f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 108303-108312 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3436681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436681","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5837121672","display_name":null,"funder_award_id":"IT27239","funder_id":"https://openalex.org/F4320322675","funder_display_name":"Mitacs"}],"funders":[{"id":"https://openalex.org/F4320322675","display_name":"Mitacs","ror":"https://ror.org/00cjrc276"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1583948418","https://openalex.org/W1644641054","https://openalex.org/W1920022804","https://openalex.org/W1982192774","https://openalex.org/W2211722331","https://openalex.org/W2556802233","https://openalex.org/W2654354136","https://openalex.org/W2786672974","https://openalex.org/W2789756826","https://openalex.org/W2798998662","https://openalex.org/W2799162093","https://openalex.org/W2902078856","https://openalex.org/W2903041390","https://openalex.org/W2945770468","https://openalex.org/W2950852430","https://openalex.org/W2953364769","https://openalex.org/W2963125977","https://openalex.org/W2963182550","https://openalex.org/W2963231572","https://openalex.org/W2963263347","https://openalex.org/W2963509914","https://openalex.org/W2963727135","https://openalex.org/W2979750740","https://openalex.org/W2981440248","https://openalex.org/W2990613095","https://openalex.org/W2991284067","https://openalex.org/W2995445811","https://openalex.org/W3008539688","https://openalex.org/W3013120860","https://openalex.org/W3014418864","https://openalex.org/W3024505128","https://openalex.org/W3034239841","https://openalex.org/W3034303554","https://openalex.org/W3038220267","https://openalex.org/W3105826707","https://openalex.org/W3108686274","https://openalex.org/W3109646990","https://openalex.org/W3111535274","https://openalex.org/W3153465022","https://openalex.org/W3158405343","https://openalex.org/W3183430956","https://openalex.org/W3184692854","https://openalex.org/W3193961581","https://openalex.org/W3195846826","https://openalex.org/W3215371923","https://openalex.org/W4221082158","https://openalex.org/W4221160819","https://openalex.org/W4229025277","https://openalex.org/W4281652610","https://openalex.org/W4281711015","https://openalex.org/W4290991313","https://openalex.org/W4309103398","https://openalex.org/W4312903973","https://openalex.org/W4318187643","https://openalex.org/W4320036973","https://openalex.org/W4361213447","https://openalex.org/W4385245566","https://openalex.org/W4386066101","https://openalex.org/W4397030879","https://openalex.org/W6726497184","https://openalex.org/W6739778489","https://openalex.org/W6747381837","https://openalex.org/W6748816842","https://openalex.org/W6763422710","https://openalex.org/W6796566654","https://openalex.org/W6801038080","https://openalex.org/W6810249204","https://openalex.org/W6839446344","https://openalex.org/W6974146666"],"related_works":["https://openalex.org/W2093262417","https://openalex.org/W2123131699","https://openalex.org/W4377865163","https://openalex.org/W4313588532","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Point":[0],"cloud-based":[1],"deep":[2],"neural":[3],"networks":[4],"(PC-DNNs)":[5],"has":[6,37],"seen":[7],"growing":[8],"interest":[9],"in":[10],"the":[11,53,68,71,83],"construction":[12],"domain":[13],"due":[14,81],"to":[15,19,46,82],"their":[16],"remarkable":[17],"ability":[18],"enhance":[20],"Building":[21],"Information":[22],"Modeling":[23],"(BIM)-related":[24],"tasks.":[25],"Among":[26],"these":[27],"tasks,":[28],"Industry":[29],"Foundation":[30],"Classes":[31],"(IFC)":[32],"object":[33,76,116],"classification":[34,48],"using":[35],"PC-DNNs":[36],"become":[38],"an":[39],"active":[40],"research":[41],"topic.":[42],"This":[43,78],"focus":[44],"aims":[45],"mitigate":[47],"discrepancies":[49],"that":[50,97],"occur":[51],"during":[52],"interoperability":[54],"of":[55,70,89,124],"BIM":[56],"tools":[57],"for":[58,74,114],"information":[59],"exchange.":[60],"However,":[61],"existing":[62],"studies":[63],"have":[64],"not":[65,99],"fully":[66],"investigated":[67],"potential":[69],"PC-DNN":[72,90,112,127],"models":[73,91,113],"IFC":[75,115,133,138],"classification.":[77,117],"limitation":[79],"is":[80],"reliance":[84],"on":[85,93],"a":[86,121,146],"limited":[87],"number":[88],"trained":[92],"small,":[94],"private":[95],"datasets":[96],"are":[98],"openly":[100],"accessible.":[101],"To":[102],"address":[103],"this":[104,107],"knowledge":[105],"gap,":[106],"study":[108,119],"evaluates":[109],"diverse":[110],"state-of-the-art":[111],"Our":[118],"provides":[120],"comprehensive":[122],"analysis":[123],"how":[125],"different":[126],"components":[128],"and":[129,141,158],"loss":[130],"functions":[131],"affect":[132],"classification,":[134],"utilizing":[135],"two":[136],"public":[137],"datasets:":[139],"IFCNet":[140],"BIMGEOM.":[142],"Experimental":[143],"results":[144],"offer":[145],"detailed":[147],"comparison":[148],"across":[149],"metrics":[150],"such":[151],"as":[152],"accuracy,":[153],"learning":[154],"progression,":[155],"computation":[156],"time,":[157],"model":[159],"parameters.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}