{"id":"https://openalex.org/W4320496975","doi":"https://doi.org/10.3390/rs15040982","title":"Data Preparation Impact on Semantic Segmentation of 3D Mobile LiDAR Point Clouds Using Deep Neural Networks","display_name":"Data Preparation Impact on Semantic Segmentation of 3D Mobile LiDAR Point Clouds Using Deep Neural Networks","publication_year":2023,"publication_date":"2023-02-10","ids":{"openalex":"https://openalex.org/W4320496975","doi":"https://doi.org/10.3390/rs15040982"},"language":"en","primary_location":{"id":"doi:10.3390/rs15040982","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15040982","pdf_url":"https://www.mdpi.com/2072-4292/15/4/982/pdf?version=1676022194","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/4/982/pdf?version=1676022194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062386012","display_name":"Reza Mahmoudi Kouhi","orcid":"https://orcid.org/0009-0008-6539-8749"},"institutions":[{"id":"https://openalex.org/I43406934","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03","country_code":"CA","type":"education","lineage":["https://openalex.org/I43406934"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Reza Mahmoudi Kouhi","raw_affiliation_strings":["Department of Geomatics Sciences, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Geomatics Sciences, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada","institution_ids":["https://openalex.org/I43406934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083402994","display_name":"Sylvie Daniel","orcid":"https://orcid.org/0000-0003-2383-9442"},"institutions":[{"id":"https://openalex.org/I43406934","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03","country_code":"CA","type":"education","lineage":["https://openalex.org/I43406934"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sylvie Daniel","raw_affiliation_strings":["Department of Geomatics Sciences, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Geomatics Sciences, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada","institution_ids":["https://openalex.org/I43406934"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032902130","display_name":"Philippe Gigu\u00e8re","orcid":"https://orcid.org/0000-0002-7520-8290"},"institutions":[{"id":"https://openalex.org/I43406934","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03","country_code":"CA","type":"education","lineage":["https://openalex.org/I43406934"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Philippe Gigu\u00e8re","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Universit\u00e9 Laval, Qu\u00e9bec City, QC G1V 0A6, Canada","institution_ids":["https://openalex.org/I43406934"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062386012"],"corresponding_institution_ids":["https://openalex.org/I43406934"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.249,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73600068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"15","issue":"4","first_page":"982","last_page":"982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.998199999332428,"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":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8331125974655151},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8180530071258545},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5928707718849182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5920991897583008},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5869594216346741},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5644389390945435},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5475292801856995},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.546691358089447},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5429548621177673},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.43826955556869507},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42180347442626953},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40551725029945374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3745172321796417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25043201446533203},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.1715172529220581}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8331125974655151},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8180530071258545},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5928707718849182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5920991897583008},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5869594216346741},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5644389390945435},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5475292801856995},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.546691358089447},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5429548621177673},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.43826955556869507},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42180347442626953},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40551725029945374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3745172321796417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25043201446533203},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.1715172529220581},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15040982","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15040982","pdf_url":"https://www.mdpi.com/2072-4292/15/4/982/pdf?version=1676022194","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1005313ea85f48f6b25fbebe194e7625","is_oa":true,"landing_page_url":"https://doaj.org/article/1005313ea85f48f6b25fbebe194e7625","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 4, p 982 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/4/982/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15040982","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15040982","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15040982","pdf_url":"https://www.mdpi.com/2072-4292/15/4/982/pdf?version=1676022194","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G1597412403","display_name":null,"funder_award_id":"RGPIN-","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G2165548363","display_name":null,"funder_award_id":"Canada","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G2417676328","display_name":null,"funder_award_id":"RGPIN-2018-0","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G2980479518","display_name":null,"funder_award_id":"RGPIN-2018","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G3216283581","display_name":null,"funder_award_id":"RGPIN-201","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G6104643682","display_name":null,"funder_award_id":"RGPIN-2018-04046","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G6221715925","display_name":null,"funder_award_id":"RGPIN","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G8284766523","display_name":null,"funder_award_id":"(NSERC)","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320310137","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03"},{"id":"https://openalex.org/F4320314000","display_name":"Compute Canada","ror":"https://ror.org/03ty8yr27"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4320496975.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2062478318","https://openalex.org/W2460657278","https://openalex.org/W2556802233","https://openalex.org/W2609719703","https://openalex.org/W2624503621","https://openalex.org/W2737234477","https://openalex.org/W2761129952","https://openalex.org/W2770046775","https://openalex.org/W2775216572","https://openalex.org/W2788158258","https://openalex.org/W2798297823","https://openalex.org/W2798998662","https://openalex.org/W2806332096","https://openalex.org/W2887121482","https://openalex.org/W2894567022","https://openalex.org/W2938428612","https://openalex.org/W2950642167","https://openalex.org/W2955472583","https://openalex.org/W2962701877","https://openalex.org/W2963125977","https://openalex.org/W2963158438","https://openalex.org/W2963706542","https://openalex.org/W2963727135","https://openalex.org/W2964257316","https://openalex.org/W2965803762","https://openalex.org/W2979750740","https://openalex.org/W2981199548","https://openalex.org/W2986519121","https://openalex.org/W3003257820","https://openalex.org/W3012494314","https://openalex.org/W3039448353","https://openalex.org/W3041660378","https://openalex.org/W3049239917","https://openalex.org/W3103830808","https://openalex.org/W3105297345","https://openalex.org/W3122633743","https://openalex.org/W3124633807","https://openalex.org/W4214755140","https://openalex.org/W4235490688","https://openalex.org/W4243863038","https://openalex.org/W6747904511","https://openalex.org/W6910779650"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W4281783339","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W4313588532"],"abstract_inverted_index":{"Currently,":[0],"3D":[1,14,48,132,264],"point":[2,22,49,134,164,266],"clouds":[3,23,267],"are":[4,24,79,124],"being":[5],"used":[6],"widely":[7,232],"due":[8],"to":[9,112,145,202,243,255],"their":[10,147],"reliability":[11],"in":[12,130,167],"presenting":[13],"objects":[15],"and":[16,26,177,259],"accurately":[17],"localizing":[18],"them.":[19],"However,":[20],"raw":[21],"unstructured":[25],"do":[27],"not":[28],"contain":[29],"semantic":[30,45],"information":[31],"about":[32],"the":[33,44,57,60,63,76,82,85,95,102,155,186,192,203,213,217,235,244,269],"objects.":[34],"Recently,":[35],"dedicated":[36],"deep":[37,105,150,173,272],"neural":[38,106,151,174,273],"networks":[39,196],"have":[40,93],"been":[41,54],"proposed":[42,187,207],"for":[43,220,226],"segmentation":[46],"of":[47,59,65,84,97,104,185,194,261,271],"clouds.":[50,135],"The":[51,179,205],"focus":[52],"has":[53],"put":[55],"on":[56,101,149,163],"architecture":[58],"network,":[61],"while":[62],"performance":[64,103,193,241],"some":[66],"networks,":[67],"such":[68],"as":[69],"Kernel":[70],"Point":[71],"Convolution":[72],"(KPConv),":[73],"shows":[74],"that":[75,123,182],"way":[77],"data":[78,99,120,142,188,209,237],"presented":[80],"at":[81,268],"input":[83,270],"network":[86],"is":[87],"also":[88,137],"important.":[89],"Few":[90],"prior":[91],"works":[92],"studied":[94],"impact":[96,148],"using":[98,183],"preparation":[100,121,143,189,210,238],"networks.":[107,152,222,274],"Therefore,":[108],"our":[109],"goal":[110],"was":[111],"address":[113],"this":[114,250],"issue.":[115],"We":[116,136,153,169,223],"propose":[117],"two":[118,139,172,206],"novel":[119,208],"methods":[122,144,157,190,211,219],"compatible":[125],"with":[126,158,171,231],"typical":[127],"density":[128],"variations":[129],"outdoor":[131,263],"LiDAR":[133,265],"investigated":[138,218],"already":[140],"existing":[141],"show":[146],"compared":[154,201,242],"four":[156],"a":[159,198],"baseline":[160],"method":[161],"based":[162],"cloud":[165],"partitioning":[166,260],"PointNet++.":[168],"experimented":[170],"networks:":[175],"PointNet++":[176],"KPConv.":[178],"results":[180,215],"showed":[181],"any":[184],"improved":[191],"both":[195,221],"by":[197],"tangible":[199],"margin":[200],"baseline.":[204],"achieved":[212],"best":[214],"among":[216],"noticed":[224],"that,":[225],"datasets":[227],"containing":[228],"many":[229],"classes":[230],"varying":[233],"sizes,":[234],"KNN-based":[236],"offered":[239],"superior":[240],"Fixed":[245],"Radius":[246],"(FR)":[247],"method.":[248],"Moreover,":[249],"research":[251],"allowed":[252],"identifying":[253],"guidelines":[254],"select":[256],"meaningful":[257],"downsampling":[258],"large-scale":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-19T08:26:33.389920","created_date":"2025-10-10T00:00:00"}
