{"id":"https://openalex.org/W4405895875","doi":"https://doi.org/10.1109/tgrs.2024.3524212","title":"Cross-Domain Incremental Feature Learning for ALS Point Cloud Semantic Segmentation With Few Samples","display_name":"Cross-Domain Incremental Feature Learning for ALS Point Cloud Semantic Segmentation With Few Samples","publication_year":2024,"publication_date":"2024-12-30","ids":{"openalex":"https://openalex.org/W4405895875","doi":"https://doi.org/10.1109/tgrs.2024.3524212"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3524212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3524212","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/A5009943113","display_name":"Mofan Dai","orcid":"https://orcid.org/0000-0002-9843-4100"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mofan Dai","raw_affiliation_strings":["School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9843-4100","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109223333","display_name":"Shuai Xing","orcid":"https://orcid.org/0009-0008-5766-2650"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Xing","raw_affiliation_strings":["School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-5766-2650","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100863825","display_name":"Qing Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Xu","raw_affiliation_strings":["School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432317","display_name":"Pengcheng Li","orcid":"https://orcid.org/0000-0002-5695-9304"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Li","raw_affiliation_strings":["School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101286743","display_name":"Jiechen Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiechen Pan","raw_affiliation_strings":["School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0009-8305-7136","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071855633","display_name":"Hanyun Wang","orcid":"https://orcid.org/0000-0002-8320-4230"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanyun Wang","raw_affiliation_strings":["Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains and the Key Laboratory of Spatiotemporal Information Perception and Fusion Technology, Ministry of Land and Resources, Zhengzhou, Henan, China","School of Surveying and Mapping, Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8320-4230","affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains and the Key Laboratory of Spatiotemporal Information Perception and Fusion Technology, Ministry of Land and Resources, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"School of Surveying and Mapping, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3295,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56222171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"63","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":0.9462000131607056,"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":0.9462000131607056,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9323999881744385,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9120000004768372,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7011306285858154},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6980368494987488},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.617180585861206},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5753517746925354},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5569536089897156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5050936341285706},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.49058762192726135},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43561217188835144},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3919112980365753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3897658586502075},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2415255606174469},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08849132061004639}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7011306285858154},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6980368494987488},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.617180585861206},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5753517746925354},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5569536089897156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5050936341285706},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.49058762192726135},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43561217188835144},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3919112980365753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3897658586502075},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2415255606174469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08849132061004639},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3524212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3524212","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W2102673432","https://openalex.org/W2108598243","https://openalex.org/W2473930607","https://openalex.org/W2560609797","https://openalex.org/W2788388592","https://openalex.org/W2948734064","https://openalex.org/W2964189064","https://openalex.org/W2968557240","https://openalex.org/W2979750740","https://openalex.org/W2981199548","https://openalex.org/W2981864462","https://openalex.org/W2982410595","https://openalex.org/W2990613095","https://openalex.org/W3012494314","https://openalex.org/W3034856281","https://openalex.org/W3035739565","https://openalex.org/W3035750252","https://openalex.org/W3036406207","https://openalex.org/W3046698617","https://openalex.org/W3084053805","https://openalex.org/W3090558831","https://openalex.org/W3091848145","https://openalex.org/W3111535274","https://openalex.org/W3133884127","https://openalex.org/W3153635465","https://openalex.org/W3163179572","https://openalex.org/W3167071962","https://openalex.org/W3168377947","https://openalex.org/W3176802407","https://openalex.org/W3177015573","https://openalex.org/W3195577467","https://openalex.org/W3198159964","https://openalex.org/W3202349074","https://openalex.org/W3202541643","https://openalex.org/W3216568609","https://openalex.org/W4200630932","https://openalex.org/W4206533545","https://openalex.org/W4214755140","https://openalex.org/W4221138238","https://openalex.org/W4312289694","https://openalex.org/W4312317653","https://openalex.org/W4312401240","https://openalex.org/W4312664299","https://openalex.org/W4312699854","https://openalex.org/W4313534927","https://openalex.org/W4321482463","https://openalex.org/W4372283849","https://openalex.org/W4379780990","https://openalex.org/W4380723689","https://openalex.org/W4384080551","https://openalex.org/W4385801109","https://openalex.org/W4386075508","https://openalex.org/W4386076196","https://openalex.org/W4386083124","https://openalex.org/W4386598267","https://openalex.org/W4391696916","https://openalex.org/W6736057607","https://openalex.org/W6738602802","https://openalex.org/W6739778489","https://openalex.org/W6750109254","https://openalex.org/W6753266022","https://openalex.org/W6767325187","https://openalex.org/W6789755465","https://openalex.org/W6793352155","https://openalex.org/W6846794945","https://openalex.org/W6863004808"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4399442168","https://openalex.org/W2114282491","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Feature":[0],"learning":[1,56,86,92,156,190],"of":[2],"airborne":[3],"laser":[4],"scanning":[5],"(ALS)":[6],"point":[7,44,74,100,169,208],"clouds":[8],"is":[9],"challenged":[10],"by":[11,69],"both":[12],"the":[13,71,83,89,104,111,132,143,204],"limited":[14,35],"annotated":[15],"samples":[16],"and":[17,31,50,88,94,128,152,174],"imbalanced":[18],"class":[19],"distribution.":[20],"An":[21],"intuitive":[22],"way":[23],"involves":[24],"pretraining":[25],"on":[26,33,166,199,206],"a":[27,34,97,153],"well-annotated":[28,98],"source":[29,105,127],"dataset":[30,102,145],"fine-tuning":[32],"target":[36,129,144],"dataset.":[37,106],"However,":[38],"cross-domain":[39,72,84,181],"challenges":[40],"such":[41],"as":[42,103],"heterogeneous":[43],"cloud":[45,75,101,170,209],"density,":[46],"varying":[47],"terrain":[48],"features,":[49],"inconsistent":[51],"object":[52],"categories":[53,122,138],"complicate":[54],"transfer":[55,85],"for":[57],"3-D":[58],"land":[59],"cover":[60],"classification.":[61],"In":[62],"this":[63],"article,":[64],"we":[65,95],"address":[66],"these":[67],"issues":[68],"separating":[70],"ALS":[73,168,207],"semantic":[76,154],"segmentation":[77],"into":[78],"two":[79],"subsequent":[80],"subtasks,":[81],"i.e.,":[82],"subtask":[87,113,134],"intradomain":[90],"class-incremental":[91],"subtask,":[93],"use":[96],"photogrammetric":[99],"To":[107],"mitigate":[108],"domain":[109,115],"discrepancies,":[110],"first":[112],"employs":[114],"adversarial":[116,155],"training":[117],"to":[118],"learn":[119],"from":[120],"base":[121,160],"that":[123,139],"are":[124,140],"shared":[125],"between":[126],"datasets.":[130],"Then,":[131],"second":[133],"incrementally":[135],"learns":[136],"new":[137],"specific":[141],"within":[142],"using":[146],"an":[147],"incremental":[148],"feature-semantic":[149],"distillation":[150],"module":[151,157],"while":[158],"retaining":[159],"category":[161],"knowledge.":[162],"Experimental":[163],"results":[164],"evaluated":[165],"three":[167],"datasets":[171],"(ISPRS,":[172],"DALES,":[173],"H3D)":[175],"with":[176,183,188],"different":[177],"semantics":[178],"show":[179],"state-of-the-art":[180],"performance":[182],"few":[184],"labeled":[185],"samples.":[186],"Compared":[187],"few-shot":[189],"methods,":[191],"our":[192],"method":[193],"shows":[194],"promising":[195],"generalization":[196],"ability":[197],"particularly":[198],"domain-specific":[200],"categories,":[201],"greatly":[202],"alleviating":[203],"dependence":[205],"annotations.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
