{"id":"https://openalex.org/W3137322777","doi":null,"title":"A comparative study of deep learning methods for building footprints detection using high spatial resolution aerial images","display_name":"A comparative study of deep learning methods for building footprints detection using high spatial resolution aerial images","publication_year":2021,"publication_date":"2021-03-16","ids":{"openalex":"https://openalex.org/W3137322777","mag":"3137322777"},"language":"en","primary_location":{"id":"mag:3137322777","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2103.09300","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.09300","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049403375","display_name":"Hongjie He","orcid":"https://orcid.org/0000-0003-3839-5821","observed_orcids":["https://orcid.org/0000-0003-3839-5821"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongjie He","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3839-5821","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037028903","display_name":"Ke Yang","orcid":"https://orcid.org/0000-0001-6617-9558","observed_orcids":["https://orcid.org/0000-0001-6617-9558"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Yang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6617-9558","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101739054","display_name":"Yuwei Cai","orcid":"https://orcid.org/0000-0002-7312-3031","observed_orcids":["https://orcid.org/0000-0002-7312-3031"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuwei Cai","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7312-3031","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021029596","display_name":"Zijian Jiang","orcid":"https://orcid.org/0000-0002-0537-8817","observed_orcids":["https://orcid.org/0000-0002-0537-8817"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zijian Jiang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0537-8817","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114096788","display_name":"Qiutong Yu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiutong Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101803331","display_name":"Kun Zhao","orcid":"https://orcid.org/0000-0001-5260-4170","observed_orcids":["https://orcid.org/0000-0001-5260-4170"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Zhao","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5260-4170","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372762","display_name":"Jun-Bo Wang","orcid":"https://orcid.org/0000-0002-1881-3558","observed_orcids":["https://orcid.org/0000-0002-1881-3558"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun-Bo Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1881-3558","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061612965","display_name":"Sarah Narges Fatholahi","orcid":"https://orcid.org/0000-0001-9757-6783","observed_orcids":["https://orcid.org/0000-0001-9757-6783"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarah Narges Fatholahi","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9757-6783","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Liu","orcid":"https://orcid.org/0000-0003-4242-4840","observed_orcids":["https://orcid.org/0000-0003-4242-4840"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4242-4840","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006763919","display_name":"Hasti Andon Petrosians","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasti Andon Petrosians","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033279910","display_name":"Bingxu Hu","orcid":"https://orcid.org/0009-0005-7935-4892","observed_orcids":["https://orcid.org/0009-0005-7935-4892"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bingxu Hu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022167049","display_name":"Liyuan Qing","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liyuan Qing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042989803","display_name":"Zhehan Zhang","orcid":"https://orcid.org/0000-0003-4707-1730","observed_orcids":["https://orcid.org/0000-0003-4707-1730"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhehan Zhang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4707-1730","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017266329","display_name":"Hongzhang Xu","orcid":"https://orcid.org/0000-0002-6407-3917","observed_orcids":["https://orcid.org/0000-0002-6407-3917"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongzhang Xu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6407-3917","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436429","display_name":"Siyu Li","orcid":"https://orcid.org/0000-0001-8468-5366","observed_orcids":["https://orcid.org/0000-0001-8468-5366","https://orcid.org/0000-0002-4326-7560","https://orcid.org/0000-0002-5675-4114","https://orcid.org/0009-0005-6543-5077"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siyu Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8468-5366","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034166335","display_name":"Linlin Xu","orcid":"https://orcid.org/0000-0002-3488-5199","observed_orcids":["https://orcid.org/0000-0002-3488-5199"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Linlin Xu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-3488-5199","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100613889","display_name":"Jonathan Li","orcid":"https://orcid.org/0000-0001-7899-0049","observed_orcids":["https://orcid.org/0000-0001-7899-0049"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jonathan Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7899-0049","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.0,"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/building-footprint-extraction","display_name":"building footprint extraction","score":0.8140000104904175},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.8659999966621399},{"id":"https://openalex.org/keywords/deeplabv3","display_name":"DeepLabV3+","score":0.9589999914169312},{"id":"https://openalex.org/keywords/u-net","display_name":"U-Net","score":0.9760000109672546},{"id":"https://openalex.org/keywords/fcn-8s","display_name":"FCN-8s","score":0.9860000014305115},{"id":"https://openalex.org/keywords/training-set-size","display_name":"training data size","score":0.9049999713897705},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.5950000286102295},{"id":"https://openalex.org/keywords/urban-mapping","display_name":"urban cartography","score":0.6790000200271606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7324753999710083},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6551343202590942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6296296119689941},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.49691393971443176},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.48321449756622314},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4807548224925995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46262598037719727},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43886175751686096},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4232249855995178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4088415801525116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3533855080604553},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2707243859767914},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23983514308929443},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.157649427652359},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3137322777","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2103.09300","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3137322777","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2103.09300","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1966411833","https://openalex.org/W2173290281","https://openalex.org/W2630837129","https://openalex.org/W2781474777","https://openalex.org/W3000652771","https://openalex.org/W3019847943"],"related_works":["https://openalex.org/W4280522787","https://openalex.org/W6930454841","https://openalex.org/W4214555059","https://openalex.org/W4390066851","https://openalex.org/W4309346524","https://openalex.org/W4379619900","https://openalex.org/W4410743009","https://openalex.org/W4281756502","https://openalex.org/W7140073892","https://openalex.org/W6922074832"],"abstract_inverted_index":{"Building":[0],"footprints":[1,30,36,59,71],"data":[2,108,119,133],"is":[3,48,136],"of":[4,43,69,102,118,124],"importance":[5],"in":[6,57,111,131,177],"several":[7],"urban":[8],"applications":[9],"and":[10,19,38,97,146,154,162],"natural":[11],"disaster":[12],"management.":[13],"In":[14,82,165],"contrast":[15],"to":[16,52,114,121],"traditional":[17],"surveying":[18],"mapping,":[20],"using":[21,78],"high":[22,74],"spatial":[23,75],"resolution":[24,76],"aerial":[25],"images,":[26],"deep":[27,44,79],"learning-based":[28,80],"building":[29,35,58,70],"extraction":[31,72,178],"methods":[32],"can":[33],"extract":[34],"accurately":[37],"efficiently.":[39],"With":[40],"rapidly":[41],"development":[42],"learning":[45],"methods,":[46,90],"it":[47],"hard":[49],"for":[50],"novice":[51],"harness":[53],"the":[54,66,87,100,103,107,116,122,125,137,143,151,159],"powerful":[55],"tools":[56],"extraction.":[60],"The":[61,127],"paper":[62],"aims":[63],"at":[64],"providing":[65],"whole":[67],"process":[68],"from":[73],"images":[77],"methods.":[81],"addition,":[83,166],"we":[84,105],"also":[85],"compare":[86],"commonly":[88],"used":[89,110],"including":[91],"Fully":[92],"Convolutional":[93],"Networks":[94],"(FCN)-8s,":[95],"U-Net":[96,157],"DeepLabv3+.":[98],"At":[99],"end":[101],"work,":[104],"change":[106],"size":[109,120],"models":[112],"training":[113,169],"explore":[115],"influence":[117],"performance":[123],"algorithms.":[126],"experiments":[128],"show":[129],"that,":[130],"different":[132],"size,":[134],"DeepLabv3+":[135],"best":[138],"algorithm":[139],"among":[140],"them":[141],"with":[142,167,174],"highest":[144,155],"accuracy":[145,153,161,176],"moderate":[147,160],"efficiency;":[148,156],"FCN-8s":[149],"has":[150],"worst":[152],"shows":[158],"lowest":[163],"efficiency.":[164],"more":[168],"data,":[170],"algorithms":[171],"converged":[172],"faster":[173],"higher":[175],"results.":[179]},"counts_by_year":[],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2021-03-29T00:00:00"}
