{"id":"https://openalex.org/W4380303698","doi":"https://doi.org/10.1109/tgrs.2023.3285207","title":"Recurrent Residual Dual Attention Network for Airborne Laser Scanning Point Cloud Semantic Segmentation","display_name":"Recurrent Residual Dual Attention Network for Airborne Laser Scanning Point Cloud Semantic Segmentation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4380303698","doi":"https://doi.org/10.1109/tgrs.2023.3285207"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3285207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3285207","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5102786659","display_name":"Tao Zeng","orcid":"https://orcid.org/0000-0002-1661-4301"},"institutions":[{"id":"https://openalex.org/I4210110558","display_name":"Xi'an Technological University","ror":"https://ror.org/01t8prc81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Zeng","raw_affiliation_strings":["School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China","institution_ids":["https://openalex.org/I4210110558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064046752","display_name":"Fulin Luo","orcid":"https://orcid.org/0000-0002-7696-0775"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fulin Luo","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7696-0775","affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009251831","display_name":"Tan Guo","orcid":"https://orcid.org/0000-0001-9523-8094"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Guo","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-9523-8094","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008251375","display_name":"Xiuwen Gong","orcid":"https://orcid.org/0000-0002-1078-1571"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuwen Gong","raw_affiliation_strings":["Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1078-1571","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034346187","display_name":"Jingyun Xue","orcid":"https://orcid.org/0000-0001-6501-4735"},"institutions":[{"id":"https://openalex.org/I4210110558","display_name":"Xi'an Technological University","ror":"https://ror.org/01t8prc81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyun Xue","raw_affiliation_strings":["School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China","institution_ids":["https://openalex.org/I4210110558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071114999","display_name":"Hanshan Li","orcid":"https://orcid.org/0000-0002-0110-9898"},"institutions":[{"id":"https://openalex.org/I4210110558","display_name":"Xi'an Technological University","ror":"https://ror.org/01t8prc81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanshan Li","raw_affiliation_strings":["School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Xi’an Technological University, Xi’an, China","institution_ids":["https://openalex.org/I4210110558"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2848,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92434975,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994999766349792,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9983000159263611,"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":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8017253875732422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7510648369789124},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6248366832733154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.58536297082901},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5781792998313904},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5452566146850586},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4580039978027344},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4242643117904663},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38585570454597473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37642902135849},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3279564380645752},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1576085388660431},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1262437105178833}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8017253875732422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7510648369789124},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6248366832733154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.58536297082901},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5781792998313904},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5452566146850586},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4580039978027344},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4242643117904663},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38585570454597473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37642902135849},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3279564380645752},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1576085388660431},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1262437105178833},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3285207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3285207","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1722848255","display_name":null,"funder_award_id":"CSTB2022NSCQ-MSX0452","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G2532463097","display_name":"\u591a\u89c6\u56fe\u8d85\u56fe\u5377\u79ef\u7f51\u7edc\u7684\u9ad8\u5149\u8c31\u56fe\u50cf\u65e0\u76d1\u7763\u5b66\u4e60\u65b9\u6cd5\u7814\u7a76","funder_award_id":"62071340","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4480856173","display_name":null,"funder_award_id":"2023CDJXY-039","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5922005406","display_name":null,"funder_award_id":"62201109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1973644502","https://openalex.org/W2084468773","https://openalex.org/W2560609797","https://openalex.org/W2752782242","https://openalex.org/W2761129952","https://openalex.org/W2896259381","https://openalex.org/W2962880841","https://openalex.org/W2963121255","https://openalex.org/W2963351448","https://openalex.org/W2968622120","https://openalex.org/W2979750740","https://openalex.org/W2981199548","https://openalex.org/W2990613095","https://openalex.org/W3008274274","https://openalex.org/W3009401626","https://openalex.org/W3016245793","https://openalex.org/W3017360822","https://openalex.org/W3034981362","https://openalex.org/W3039448353","https://openalex.org/W3043099088","https://openalex.org/W3109646990","https://openalex.org/W3125698590","https://openalex.org/W3158097430","https://openalex.org/W3162787701","https://openalex.org/W3163821474","https://openalex.org/W3171433839","https://openalex.org/W3181190968","https://openalex.org/W3196583898","https://openalex.org/W3215916782","https://openalex.org/W3217526930","https://openalex.org/W4210344621","https://openalex.org/W4210998390","https://openalex.org/W4214521144","https://openalex.org/W4223991150","https://openalex.org/W4225759834","https://openalex.org/W4225966217","https://openalex.org/W4226099359","https://openalex.org/W4244565819","https://openalex.org/W4293354637","https://openalex.org/W4293795076","https://openalex.org/W4312616477","https://openalex.org/W4312929415","https://openalex.org/W4313145913","https://openalex.org/W4313534927","https://openalex.org/W4317553477","https://openalex.org/W4319865968","https://openalex.org/W4321022054","https://openalex.org/W4322706915","https://openalex.org/W6739778489","https://openalex.org/W6795307729","https://openalex.org/W6804061671","https://openalex.org/W6807511073"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W4389574804","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Kernel":[0],"point":[1,8,11,36,67,79,198],"convolution":[2,80,139],"(KPConv)":[3],"can":[4,185],"effectively":[5],"represent":[6],"the":[7,19,31,58,62,71,93,100,115,120,142,149,154,162,165,177,192],"features":[9],"of":[10,22,34,65,88,164,168,196],"cloud":[12,68],"data.":[13,69],"However,":[14],"KPConv-based":[15],"methods":[16],"just":[17],"consider":[18],"local":[20,116,128,137,145],"information":[21,146],"each":[23],"point,":[24],"which":[25],"is":[26],"very":[27],"difficult":[28],"to":[29,91,103,112,140,160,175,190,212,217],"characterize":[30],"intrinsic":[32],"properties":[33],"ALS":[35,66,197,206],"clouds":[37],"for":[38,61],"complex":[39],"laser":[40],"scanning":[41],"conditions.":[42],"Therefore,":[43],"we":[44,74,98,123,171],"rethink":[45],"KPConv":[46],"and":[47,127,136,144,153,210],"propose":[48],"a":[49,85,105,125,218],"recurrent":[50,106],"residual":[51,107],"dual":[52],"attention":[53,77,109,130],"network":[54],"(RRDAN)":[55],"based":[56],"on":[57,204],"encoder-decoder":[59],"structure":[60],"semantic":[63,194],"segmentation":[64,195],"In":[70,119,158],"encoder":[72],"stage,":[73,122],"design":[75,124],"an":[76],"kernel":[78,108],"(AKPConv)":[81],"block":[82,102],"by":[83],"using":[84],"scaling":[86],"factor":[87],"batch":[89],"normalization":[90],"highlight":[92],"significant":[94],"channel":[95,129],"information.":[96],"Then,":[97],"use":[99],"AKPConv":[101],"develop":[104],"(RRKA)":[110],"module":[111,132],"iteratively":[113],"aggregate":[114],"neighborhood":[117],"features.":[118,157],"decoder":[121],"global":[126,134,143],"(GLCA)":[131],"with":[133],"connection":[135],"1D":[138],"interact":[141],"after":[147],"fusing":[148],"upsampled":[150],"high-level":[151],"representations":[152],"skip-connected":[155],"low-level":[156],"addition,":[159],"reduce":[161],"influence":[163],"long-tail":[166],"distribution":[167],"reflection":[169],"intensity,":[170],"apply":[172],"gamma":[173],"transformation":[174],"correct":[176],"data":[178],"as":[179],"normal":[180],"distribution.":[181],"The":[182],"proposed":[183],"RRDAN":[184],"achieve":[186],"diversified":[187],"feature":[188],"aggregation":[189],"implement":[191],"refined":[193],"clouds.":[199],"We":[200],"evaluate":[201],"our":[202],"method":[203],"two":[205],"datasets":[207],"(i.e.,":[208],"ISPRS":[209],"DCF2019)":[211],"demonstrate":[213],"its":[214],"performance":[215],"compared":[216],"few":[219],"advanced":[220],"methods.":[221],"Code:":[222],"https://github.com/SC-shendazt/RRDAN.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}