{"id":"https://openalex.org/W4285178246","doi":"https://doi.org/10.1109/tgrs.2022.3174399","title":"POI Detection of High-Rise Buildings Using Remote Sensing Images: A Semantic Segmentation Method Based on Multitask Attention Res-U-Net","display_name":"POI Detection of High-Rise Buildings Using Remote Sensing Images: A Semantic Segmentation Method Based on Multitask Attention Res-U-Net","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285178246","doi":"https://doi.org/10.1109/tgrs.2022.3174399"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3174399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3174399","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/A5000632849","display_name":"Bingnan Li","orcid":"https://orcid.org/0000-0003-3417-3295"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bingnan Li","raw_affiliation_strings":["School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia","School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052 Australia"],"raw_orcid":"https://orcid.org/0000-0003-3417-3295","affiliations":[{"raw_affiliation_string":"School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052 Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034976635","display_name":"Jiuchong Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]},{"id":"https://openalex.org/I4210152823","display_name":"China Meat Research Centre","ror":"https://ror.org/05jc4yc89","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210152823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiuchong Gao","raw_affiliation_strings":["Meituan, Beijing, China","Meituan, Beijing, 100020 China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]},{"raw_affiliation_string":"Meituan, Beijing, 100020 China","institution_ids":["https://openalex.org/I4210152823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102754436","display_name":"Shuiping Chen","orcid":"https://orcid.org/0000-0002-0633-0196"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]},{"id":"https://openalex.org/I4210152823","display_name":"China Meat Research Centre","ror":"https://ror.org/05jc4yc89","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210152823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuiping Chen","raw_affiliation_strings":["Meituan, Beijing, China","Meituan, Beijing, 100020 China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]},{"raw_affiliation_string":"Meituan, Beijing, 100020 China","institution_ids":["https://openalex.org/I4210152823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077603565","display_name":"Samsung Lim","orcid":"https://orcid.org/0000-0001-9838-8960"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Samsung Lim","raw_affiliation_strings":["School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia","School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052 Australia"],"raw_orcid":"https://orcid.org/0000-0001-9838-8960","affiliations":[{"raw_affiliation_string":"School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052 Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014930690","display_name":"Hai Jiang","orcid":"https://orcid.org/0000-0003-3414-9682"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Jiang","raw_affiliation_strings":["Department of Industrial Engineering, Tsinghua University, Beijing, China","Department of Industrial Engineering, Tsinghua University, Beijing, 100084 China"],"raw_orcid":"https://orcid.org/0000-0003-3414-9682","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing, 100084 China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7434,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91265186,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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":0.7743449807167053},{"id":"https://openalex.org/keywords/footprint","display_name":"Footprint","score":0.7185754776000977},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6728273034095764},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.5781877040863037},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4685666859149933},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4198063611984253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39625751972198486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3775576949119568},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.36186981201171875},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.13280096650123596},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10882794857025146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743449807167053},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.7185754776000977},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6728273034095764},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.5781877040863037},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4685666859149933},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4198063611984253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39625751972198486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3775576949119568},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.36186981201171875},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.13280096650123596},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10882794857025146},{"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3174399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3174399","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":[{"display_name":"Sustainable cities and communities","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W416023868","https://openalex.org/W1745334888","https://openalex.org/W1764053936","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1981934656","https://openalex.org/W2058436841","https://openalex.org/W2079454091","https://openalex.org/W2089716607","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2293078015","https://openalex.org/W2300687442","https://openalex.org/W2412782625","https://openalex.org/W2518820251","https://openalex.org/W2538244214","https://openalex.org/W2548390752","https://openalex.org/W2549412929","https://openalex.org/W2609402060","https://openalex.org/W2623331213","https://openalex.org/W2630837129","https://openalex.org/W2785057145","https://openalex.org/W2787091153","https://openalex.org/W2787614951","https://openalex.org/W2792857687","https://openalex.org/W2794187036","https://openalex.org/W2795635230","https://openalex.org/W2798122215","https://openalex.org/W2803867573","https://openalex.org/W2803946774","https://openalex.org/W2888733778","https://openalex.org/W2891854043","https://openalex.org/W2895922485","https://openalex.org/W2902036000","https://openalex.org/W2906300491","https://openalex.org/W2908320224","https://openalex.org/W2915731581","https://openalex.org/W2919115771","https://openalex.org/W2939647427","https://openalex.org/W2948398204","https://openalex.org/W2963495494","https://openalex.org/W2963659230","https://openalex.org/W2963881378","https://openalex.org/W2971095420","https://openalex.org/W2981630388","https://openalex.org/W2982206001","https://openalex.org/W2998556100","https://openalex.org/W3007796610","https://openalex.org/W3022397457","https://openalex.org/W3041165598","https://openalex.org/W3047485635","https://openalex.org/W3101577715","https://openalex.org/W3104035745","https://openalex.org/W3116802286","https://openalex.org/W3129770188","https://openalex.org/W3131491648","https://openalex.org/W3135316458","https://openalex.org/W3176330035","https://openalex.org/W4200187170","https://openalex.org/W4210736635","https://openalex.org/W6631943919","https://openalex.org/W6637131181","https://openalex.org/W6638667902","https://openalex.org/W6640295612","https://openalex.org/W6739696289","https://openalex.org/W6750469568","https://openalex.org/W6755671908","https://openalex.org/W6791385567"],"related_works":["https://openalex.org/W2330537534","https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2368534554","https://openalex.org/W2362101859","https://openalex.org/W2941610985","https://openalex.org/W2148469257","https://openalex.org/W4220744166","https://openalex.org/W4226280350","https://openalex.org/W1522196789"],"abstract_inverted_index":{"A":[0],"Point-Of-Interest":[1],"(POI)":[2],"represents":[3],"a":[4,24,31,44,63,128,233],"specific":[5],"point":[6],"location":[7],"that":[8,228],"may":[9],"be":[10,28],"useful":[11],"or":[12],"interesting":[13],"for":[14,54,114,135,262],"people,":[15],"and":[16,19,46,57,142,174,208,221,238,252,258],"therefore":[17],"each":[18],"every":[20,191],"building":[21,36,78,102,140,145,172,192,249,265],"footprint":[22,79],"in":[23,52,77,104,199,245],"topographic":[25],"map":[26],"can":[27],"recognized":[29,100],"as":[30,101],"POI.":[32],"Automatic":[33],"extraction":[34,137],"of":[35,65,138,161,169,190,217,236,243,247,256,260],"footprints":[37,103,160],"using":[38,69,214],"remote":[39,148,218],"sensing":[40,149,219],"images":[41,220],"has":[42],"become":[43],"challenging":[45],"important":[47],"research":[48],"topic":[49],"which":[50,91,268],"is":[51,109],"demand":[53],"urban":[55],"planning":[56],"development.":[58],"Extensive":[59],"studies":[60],"have":[61,88],"explored":[62],"variety":[64],"semantic":[66],"segmentation":[67,95],"methods":[68],"deep":[70],"learning":[71],"algorithms":[72,84],"to":[73,87,93,111,118,157,185],"achieve":[74,270],"better":[75],"performance":[76,273],"extraction,":[80],"however":[81],"the":[82,105,136,139,143,159,162,167,170,179,187,202,248,263,271],"existing":[83],"were":[85,99],"shown":[86],"some":[89],"limitations":[90],"lead":[92],"poor":[94],"results.":[96],"Building":[97],"roofs":[98,141,173],"previous":[106],"studies.":[107],"This":[108],"prone":[110],"error":[112],"especially":[113],"high-rise":[115,163],"buildings":[116,164],"due":[117],"different":[119],"sensor":[120],"view":[121],"angles.":[122],"In":[123],"this":[124],"paper,":[125],"we":[126],"propose":[127],"multi-task":[129],"Res-U-Net":[130],"model":[131,231],"with":[132,201],"attention":[133],"mechanism":[134],"whole":[144,264],"shapes":[146],"from":[147],"images,":[150],"then":[151],"use":[152],"an":[153,253],"offset":[154],"vector":[155],"method":[156],"detect":[158],"based":[165],"on":[166],"boundaries":[168],"corresponding":[171],"shapes.":[175],"We":[176,210],"also":[177,197],"apply":[178],"online":[180],"food":[181],"delivery":[182],"(OFD)":[183],"data":[184,206,216],"parse":[186],"POI":[188],"name":[189],"footprint.":[193],"Several":[194],"strategies":[195],"are":[196],"developed":[198],"combination":[200],"proposed":[203,230],"model,":[204],"including":[205],"augmentation":[207],"post-processing.":[209],"conduct":[211],"numerical":[212],"experiments":[213],"real":[215],"OFD":[222],"historical":[223],"order":[224],"data.":[225],"Results":[226],"demonstrate":[227],"our":[229],"achieves":[232],"total":[234],"F1-score":[235,255],"77.05%":[237],"intersection":[239],"over":[240],"union":[241],"(IoU)":[242],"63.55%":[244],"terms":[246],"roof":[250],"segmentation,":[251,267],"overall":[254],"79.02%":[257],"IoU":[259],"66.05%":[261],"shape":[266],"both":[269],"best":[272],"among":[274],"all":[275],"baseline":[276],"models.":[277]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
