{"id":"https://openalex.org/W4379984978","doi":"https://doi.org/10.1109/tgrs.2023.3284995","title":"Semantic Segmentation of Spectral LiDAR Point Clouds Based on Neural Architecture Search","display_name":"Semantic Segmentation of Spectral LiDAR Point Clouds Based on Neural Architecture Search","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379984978","doi":"https://doi.org/10.1109/tgrs.2023.3284995"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3284995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3284995","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/A5101604420","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-5543-504X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043043084","display_name":"Yuanxi Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanxi Peng","raw_affiliation_strings":["State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100611977","display_name":"Zhiwen Zhang","orcid":"https://orcid.org/0000-0002-3123-8885"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Zhang","raw_affiliation_strings":["State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062506580","display_name":"Teng Li","orcid":"https://orcid.org/0000-0002-5175-0819"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Li","raw_affiliation_strings":["College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, China","Beijing Institute for Advanced Study, National University of Defense Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Beijing Institute for Advanced Study, National University of Defense Technology, Beijing, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101604420"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":1.2263,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.75840979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9969000220298767,"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":0.9954000115394592,"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":0.8323343396186829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7855638265609741},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6729845404624939},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6170417666435242},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4810493290424347},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4713073670864105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46875524520874023},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.44512930512428284},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4157508313655853},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41241276264190674},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.38518109917640686},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2819215953350067},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20952275395393372}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8323343396186829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855638265609741},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6729845404624939},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6170417666435242},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4810493290424347},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4713073670864105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46875524520874023},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.44512930512428284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4157508313655853},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41241276264190674},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.38518109917640686},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2819215953350067},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20952275395393372},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3284995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3284995","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":[],"awards":[{"id":"https://openalex.org/G121302408","display_name":null,"funder_award_id":"91948303-1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3151452821","display_name":null,"funder_award_id":"61906210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4444537753","display_name":null,"funder_award_id":"12002380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4998861757","display_name":null,"funder_award_id":"62101575","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6586189173","display_name":null,"funder_award_id":"61803375","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8803277762","display_name":null,"funder_award_id":"2021ZD0140301","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G885265327","display_name":null,"funder_award_id":"62106278","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1625390266","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2471941257","https://openalex.org/W2472003871","https://openalex.org/W2553303224","https://openalex.org/W2555624569","https://openalex.org/W2560609797","https://openalex.org/W2606520626","https://openalex.org/W2610817424","https://openalex.org/W2724542434","https://openalex.org/W2761129952","https://openalex.org/W2770997764","https://openalex.org/W2775040228","https://openalex.org/W2778633128","https://openalex.org/W2790308185","https://openalex.org/W2798777114","https://openalex.org/W2798886737","https://openalex.org/W2807072713","https://openalex.org/W2885311373","https://openalex.org/W2891778567","https://openalex.org/W2896259381","https://openalex.org/W2922416509","https://openalex.org/W2947295162","https://openalex.org/W2954258401","https://openalex.org/W2962746461","https://openalex.org/W2963053547","https://openalex.org/W2963121255","https://openalex.org/W2963158438","https://openalex.org/W2963231572","https://openalex.org/W2963281829","https://openalex.org/W2963351448","https://openalex.org/W2963509914","https://openalex.org/W2964015378","https://openalex.org/W2964081807","https://openalex.org/W2979750740","https://openalex.org/W2981199548","https://openalex.org/W2985228975","https://openalex.org/W2990280452","https://openalex.org/W2990613095","https://openalex.org/W3008274274","https://openalex.org/W3012494314","https://openalex.org/W3016245793","https://openalex.org/W3034239841","https://openalex.org/W3035398346","https://openalex.org/W3106250896","https://openalex.org/W3107479685","https://openalex.org/W3109154950","https://openalex.org/W3153131045","https://openalex.org/W3171648433","https://openalex.org/W3174562789","https://openalex.org/W3207531210","https://openalex.org/W4214521144","https://openalex.org/W4225365663","https://openalex.org/W4235587621","https://openalex.org/W4249432839","https://openalex.org/W4293472597","https://openalex.org/W4293795076","https://openalex.org/W4295185264","https://openalex.org/W4306248206","https://openalex.org/W6639824700","https://openalex.org/W6720695503","https://openalex.org/W6726873649","https://openalex.org/W6729956949","https://openalex.org/W6729972426","https://openalex.org/W6737283639","https://openalex.org/W6739778489","https://openalex.org/W6747545098","https://openalex.org/W6753278433","https://openalex.org/W6754899465","https://openalex.org/W6765299845","https://openalex.org/W6766225098","https://openalex.org/W6770101963","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2594043982","https://openalex.org/W3036493597","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"Multispectral":[0],"light":[1],"detection":[2],"and":[3,20,49,62,76,117],"ranging":[4],"(LiDAR)":[5],"point":[6,54,142],"clouds,":[7],"as":[8,149],"a":[9,92,127],"new":[10],"kind":[11],"of":[12,22,38,59,87,105,120,157,191],"data,":[13,89],"can":[14,78,152],"be":[15,79],"characterized":[16],"by":[17,135],"high":[18],"consistency":[19],"integrity":[21],"spectral":[23],"information":[24],"geometric":[25,70],"data.":[26],"which":[27,151],"makes":[28],"it":[29],"beneficial":[30],"for":[31,141],"land":[32],"use":[33,165],"classification.":[34],"However,":[35],"direct":[36],"classification":[37],"multispectral":[39,184],"LiDAR":[40,185],"data":[41,46,61,99],"remains":[42],"challenging,":[43],"since":[44],"the":[45,53,57,85,98,103,106,161,166,175,182,189],"are":[47],"irregular":[48],"unordered.":[50],"By":[51],"describing":[52],"cloud":[55,143],"in":[56,108],"form":[58],"graph":[60,64,88,94,112,133,177],"using":[63,90],"convolution":[65,95,178],"to":[66,84,96,148,173],"naturally":[67],"model":[68],"local":[69],"structures\u2019":[71],"representation,":[72],"higher":[73],"processing":[74],"accuracy":[75],"efficiency":[77],"achieved.":[80],"Notably,":[81],"however,":[82],"due":[83],"complexity":[86],"only":[91],"single":[93],"learn":[97],"features":[100],"may":[101],"limit":[102],"capacity":[104],"architecture;":[107],"addition,":[109],"selecting":[110],"appropriate":[111],"convolutions":[113,134],"requires":[114],"human":[115],"expertise":[116],"massive":[118],"numbers":[119],"trials.":[121],"In":[122,160],"this":[123],"article,":[124],"we":[125,164],"propose":[126],"network":[128],"that":[129],"combines":[130],"several":[131],"outstanding":[132],"adapting":[136],"neural":[137],"architecture":[138],"search":[139,162,170],"(NAS)":[140],"segmentation,":[144],"an":[145],"approach":[146],"referred":[147],"GCNAS,":[150],"adaptively":[153],"achieve":[154],"different":[155],"levels":[156],"semantic":[158],"expression.":[159],"module,":[163],"Monte":[167],"Carlo":[168],"tree":[169],"(MCTS)":[171],"method":[172],"select":[174],"layerwise":[176],"kernels.":[179],"Experiments":[180],"on":[181],"Titan":[183],"dataset":[186],"have":[187],"verified":[188],"effectiveness":[190],"GCNAS.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}