{"id":"https://openalex.org/W3083786945","doi":"https://doi.org/10.3390/rs12182910","title":"Improved Anchor-Free Instance Segmentation for Building Extraction from High-Resolution Remote Sensing Images","display_name":"Improved Anchor-Free Instance Segmentation for Building Extraction from High-Resolution Remote Sensing Images","publication_year":2020,"publication_date":"2020-09-08","ids":{"openalex":"https://openalex.org/W3083786945","doi":"https://doi.org/10.3390/rs12182910","mag":"3083786945"},"language":"en","primary_location":{"id":"doi:10.3390/rs12182910","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12182910","pdf_url":"https://www.mdpi.com/2072-4292/12/18/2910/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/12/18/2910/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103187092","display_name":"Tong Wu","orcid":"https://orcid.org/0000-0002-5538-5118"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Wu","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"raw_orcid":"https://orcid.org/0000-0002-5538-5118","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006947125","display_name":"Yuan Hu","orcid":"https://orcid.org/0000-0003-1256-7023"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Hu","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507877","display_name":"Ling Peng","orcid":"https://orcid.org/0000-0003-2999-9252"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ling Peng","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101436099","display_name":"Ruonan Chen","orcid":"https://orcid.org/0000-0003-1758-6151"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruonan Chen","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101507877"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.6239,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.94788672,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"12","issue":"18","first_page":"2910","last_page":"2910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9995999932289124,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8851078748703003},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7125911116600037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630681753158569},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6492815613746643},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.46966326236724854},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4616718292236328},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.44887495040893555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44463518261909485},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4250308871269226},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3471382260322571},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08443713188171387}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8851078748703003},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7125911116600037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630681753158569},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6492815613746643},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.46966326236724854},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4616718292236328},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.44887495040893555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44463518261909485},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4250308871269226},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3471382260322571},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08443713188171387},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12182910","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12182910","pdf_url":"https://www.mdpi.com/2072-4292/12/18/2910/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5f5348bdf7b846d98a547e3afc8a9ed7","is_oa":true,"landing_page_url":"https://doaj.org/article/5f5348bdf7b846d98a547e3afc8a9ed7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 12, Iss 18, p 2910 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/18/2910/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12182910","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 12; Issue 18; Pages: 2910","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12182910","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12182910","pdf_url":"https://www.mdpi.com/2072-4292/12/18/2910/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8500000238418579}],"awards":[{"id":"https://openalex.org/G2815404724","display_name":null,"funder_award_id":"No.Z191100001419002","funder_id":"https://openalex.org/F4320325902","funder_display_name":"Beijing Municipal Science and Technology Commission"}],"funders":[{"id":"https://openalex.org/F4320325902","display_name":"Beijing Municipal Science and Technology Commission","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1901129140","https://openalex.org/W2010472122","https://openalex.org/W2034932500","https://openalex.org/W2052588857","https://openalex.org/W2054091530","https://openalex.org/W2065429801","https://openalex.org/W2076131212","https://openalex.org/W2145522004","https://openalex.org/W2150089019","https://openalex.org/W2155910279","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2300635092","https://openalex.org/W2412782625","https://openalex.org/W2565639579","https://openalex.org/W2742692613","https://openalex.org/W2757787776","https://openalex.org/W2787614951","https://openalex.org/W2795635230","https://openalex.org/W2802019258","https://openalex.org/W2806070179","https://openalex.org/W2884561390","https://openalex.org/W2886335102","https://openalex.org/W2888799854","https://openalex.org/W2908320224","https://openalex.org/W2920326761","https://openalex.org/W2948648905","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963857746","https://openalex.org/W2963881378","https://openalex.org/W2964241181","https://openalex.org/W2970987838","https://openalex.org/W2982770724","https://openalex.org/W2988452521","https://openalex.org/W2989604896","https://openalex.org/W2993182889","https://openalex.org/W3011481750","https://openalex.org/W3016108567","https://openalex.org/W3034681942","https://openalex.org/W3035049382","https://openalex.org/W3037317624","https://openalex.org/W3106250896","https://openalex.org/W3132424513"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4231775656","https://openalex.org/W4321487865","https://openalex.org/W2046435967","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690"],"abstract_inverted_index":{"Building":[0],"extraction":[1,126,157],"from":[2,36],"high-resolution":[3,37,130],"remote":[4,131],"sensing":[5,132],"images":[6],"plays":[7],"a":[8],"vital":[9],"part":[10],"in":[11,84,99,129,169,184],"urban":[12],"planning,":[13],"safety":[14],"supervision,":[15],"geographic":[16],"databases":[17],"updates,":[18],"and":[19,62,82,91,95,115,119,142,151,165,188],"some":[20],"other":[21,69],"applications.":[22],"Several":[23],"researches":[24],"are":[25,41],"devoted":[26],"to":[27,33,65],"using":[28],"convolutional":[29],"neural":[30],"network":[31,123,143],"(CNN)":[32],"extract":[34],"buildings":[35,128],"satellite/aerial":[38],"images.":[39,133],"There":[40],"two":[42],"major":[43],"methods,":[44,51,75],"one":[45,70],"is":[46,71],"the":[47,59,85,137,146,149,153,166],"CNN-based":[48,72],"semantic":[49],"segmentation":[50,74,108],"which":[52,76,190],"can":[53,180],"not":[54],"distinguish":[55],"different":[56,140],"objects":[57],"of":[58,127,139,148,158,186],"same":[60],"category":[61],"may":[63],"lead":[64],"edge":[66],"connection.":[67],"The":[68],"instance":[73,107],"rely":[77],"heavily":[78],"on":[79,111,145],"pre-defined":[80],"anchors,":[81],"result":[83],"highly":[86],"sensitive,":[87],"high":[88],"computation/storage":[89],"cost":[90],"imbalance":[92],"between":[93],"positive":[94],"negative":[96],"samples.":[97],"Therefore,":[98],"this":[100,170],"paper,":[101],"we":[102,135],"propose":[103],"an":[104],"improved":[105,120,167,177],"anchor-free":[106],"method":[109,179],"based":[110],"CenterMask":[112,168,178],"with":[113],"spatial":[114],"channel":[116],"attention-guided":[117],"mechanisms":[118],"effective":[121],"backbone":[122],"for":[124,155],"accurate":[125],"Then":[134],"analyze":[136],"influence":[138],"parameters":[141],"structure":[144],"performance":[147,154,183,193],"model,":[150],"compare":[152],"building":[156],"Mask":[159,161],"R-CNN,":[160,163],"Scoring":[162],"CenterMask,":[164],"paper.":[171],"Experimental":[172],"results":[173],"show":[174],"that":[175],"our":[176],"successfully":[181],"well-balanced":[182],"terms":[185],"speed":[187],"accuracy,":[189],"achieves":[191],"state-of-the-art":[192],"at":[194],"real-time":[195],"speed.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":14}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2020-09-14T00:00:00"}
