{"id":"https://openalex.org/W4306399487","doi":"https://doi.org/10.3390/rs14205134","title":"Multi-Feature Aggregation for Semantic Segmentation of an Urban Scene Point Cloud","display_name":"Multi-Feature Aggregation for Semantic Segmentation of an Urban Scene Point Cloud","publication_year":2022,"publication_date":"2022-10-14","ids":{"openalex":"https://openalex.org/W4306399487","doi":"https://doi.org/10.3390/rs14205134"},"language":"en","primary_location":{"id":"doi:10.3390/rs14205134","doi":"https://doi.org/10.3390/rs14205134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205134","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5134/pdf?version=1665745118","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,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/20/5134/pdf?version=1665745118","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101676576","display_name":"Jiaqing Chen","orcid":"https://orcid.org/0000-0001-9598-9701","observed_orcids":["https://orcid.org/0000-0001-9598-9701"]},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqing Chen","raw_affiliation_strings":["Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China","School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031185961","display_name":"Yindi Zhao","orcid":"https://orcid.org/0000-0002-7883-9506","observed_orcids":["https://orcid.org/0000-0002-7883-9506"]},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yindi Zhao","raw_affiliation_strings":["Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China","School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030697675","display_name":"Congtang Meng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congtang Meng","raw_affiliation_strings":["School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043414234","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0003-4706-3132","observed_orcids":["https://orcid.org/0000-0003-4706-3132"]},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5031185961"],"corresponding_institution_ids":["https://openalex.org/I211433327","https://openalex.org/I25757504"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2618},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2618},"fwci":2.4847,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.91249625,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"14","issue":"20","first_page":"5134","last_page":"5134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5102999806404114,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"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":0.5102999806404114,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4081999957561493,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.017999999225139618,"subfield":{"id":"https://openalex.org/subfields/1107","display_name":"Forestry"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud-semantic-segmentation","display_name":"point cloud semantic segmentation","score":0.925000011920929},{"id":"https://openalex.org/keywords/urban-scenes","display_name":"urban scenes","score":0.8799999952316284},{"id":"https://openalex.org/keywords/lidar-point-cloud","display_name":"LiDAR point cloud","score":0.8629999756813049},{"id":"https://openalex.org/keywords/randla-net","display_name":"RandLA-Net","score":0.9409999847412109},{"id":"https://openalex.org/keywords/multiscale-feature-fusion","display_name":"multi-scale feature fusion","score":0.7200000286102295},{"id":"https://openalex.org/keywords/dense-skip-connections","display_name":"dense skip connections","score":0.9120000004768372},{"id":"https://openalex.org/keywords/dilated-convolution","display_name":"dilated convolution","score":0.9300000071525574},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.972000002861023},{"id":"https://openalex.org/keywords/occlusion","display_name":"occlusion","score":0.6959999799728394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8014016151428223},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7510312795639038},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7353389859199524},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5165397524833679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5087526440620422},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49522915482521057},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4790133833885193},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4767806828022003},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.46657073497772217},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4289016127586365},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.41322094202041626},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3812175393104553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36402833461761475},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3421365022659302},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.31703174114227295},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.21084213256835938},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13937750458717346},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13825955986976624},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs14205134","doi":"https://doi.org/10.3390/rs14205134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205134","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5134/pdf?version=1665745118","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,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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:2a6be52927994280af92e0b74118e408","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/2a6be52927994280af92e0b74118e408","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,"listed_in":[],"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":"Remote Sensing, Vol 14, Iss 20, p 5134 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs14205134","doi":"https://doi.org/10.3390/rs14205134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205134","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5134/pdf?version=1665745118","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,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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":0.5142999887466431,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5425751367","display_name":null,"funder_award_id":"51874306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6372805087","display_name":null,"funder_award_id":"SXDJ2019","funder_id":"https://openalex.org/F4320336412","funder_display_name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336412","display_name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306399487.pdf","grobid_xml":"https://content.openalex.org/works/W4306399487.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1901129140","https://openalex.org/W1910657905","https://openalex.org/W1920022804","https://openalex.org/W2051610568","https://openalex.org/W2211722331","https://openalex.org/W2412782625","https://openalex.org/W2594519801","https://openalex.org/W2606864979","https://openalex.org/W2624503621","https://openalex.org/W2734349601","https://openalex.org/W2938428612","https://openalex.org/W2950642167","https://openalex.org/W2963333168","https://openalex.org/W2963336905","https://openalex.org/W2963351448","https://openalex.org/W2963830382","https://openalex.org/W2971311575","https://openalex.org/W2979750740","https://openalex.org/W2985276900","https://openalex.org/W2996290406","https://openalex.org/W2997724955","https://openalex.org/W3011788244","https://openalex.org/W3012494314","https://openalex.org/W3015788359","https://openalex.org/W3039448353","https://openalex.org/W3093434340","https://openalex.org/W3131291910","https://openalex.org/W3176802407","https://openalex.org/W4288003327","https://openalex.org/W4383002831"],"related_works":["https://openalex.org/W4401968374","https://openalex.org/W4389681952","https://openalex.org/W3138458448","https://openalex.org/W4400924454","https://openalex.org/W4394835938","https://openalex.org/W3196120308","https://openalex.org/W4383502315","https://openalex.org/W4308391891","https://openalex.org/W7163372342","https://openalex.org/W7125025029"],"abstract_inverted_index":{"With":[0],"the":[1,21,30,34,39,47,70,79,94,100,114,122,126,135,157,162,189,201],"rapid":[2],"development":[3,31],"of":[4,8,24,36,50,93,99,106,165,177,188],"cities,":[5],"semantic":[6,48,73,80,143],"segmentation":[7,49,74,81],"urban":[9,26,54,180],"scenes,":[10,55],"as":[11],"an":[12],"important":[13],"and":[14,33,62,84,96,103,116,128,141,160,175,191,196],"effective":[15],"imaging":[16],"method,":[17],"can":[18],"accurately":[19],"obtain":[20],"distribution":[22],"information":[23,144],"typical":[25],"ground":[27],"features,":[28],"reflecting":[29],"scale":[32],"level":[35],"greenery":[37],"in":[38,46,53],"cities.":[40],"There":[41],"are":[42],"some":[43],"challenging":[44],"problems":[45],"point":[51,71,101,183],"clouds":[52],"including":[56],"different":[57,166],"scales,":[58],"imbalanced":[59],"class":[60,171],"distribution,":[61],"missing":[63],"data":[64],"caused":[65],"by":[66],"occlusion.":[67],"Based":[68],"on":[69,121,169],"cloud":[72,184],"network":[75,88,203],"RandLA-Net,":[76],"we":[77],"propose":[78,151],"networks":[82,193],"RandLA-Net++":[83,87,190],"RandLA-Net3+.":[85],"The":[86],"is":[89,111,119,194],"a":[90,104,146],"deep":[91,97],"fusion":[92],"shallow":[95],"features":[98],"clouds,":[102],"series":[105],"nested":[107],"dense":[108],"skip":[109],"connections":[110],"used":[112],"between":[113,125],"encoder":[115,127],"decoder.":[117],"RandLA-Net3+":[118,192],"based":[120],"multi-scale":[123],"connection":[124],"decoder;":[129],"it":[130],"also":[131,150],"connects":[132],"internally":[133],"within":[134],"decoder":[136],"to":[137,155],"capture":[138],"fine-grained":[139],"details":[140],"coarse-grained":[142],"at":[145],"full":[147],"scale.":[148],"We":[149],"incorporating":[152],"dilated":[153],"convolution":[154],"increase":[156],"receptive":[158],"field":[159],"compare":[161],"improvement":[163],"effect":[164],"loss":[167],"functions":[168],"sample":[170],"imbalance.":[172],"After":[173],"verification":[174],"analysis":[176],"our":[178],"labeled":[179],"scene":[181],"LiDAR":[182],"dataset\u2014called":[185],"NJSeg-3D\u2014the":[186],"mIoU":[187],"3.4%":[195],"3.2%":[197],"higher,":[198],"respectively,":[199],"than":[200],"benchmark":[202],"RandLA-Net.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-10-17T00:00:00"}
