{"id":"https://openalex.org/W2993017798","doi":"https://doi.org/10.3390/rs11242912","title":"Accurate Building Extraction from Fused DSM and UAV Images Using a Chain Fully Convolutional Neural Network","display_name":"Accurate Building Extraction from Fused DSM and UAV Images Using a Chain Fully Convolutional Neural Network","publication_year":2019,"publication_date":"2019-12-05","ids":{"openalex":"https://openalex.org/W2993017798","doi":"https://doi.org/10.3390/rs11242912","mag":"2993017798"},"language":"en","primary_location":{"id":"doi:10.3390/rs11242912","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11242912","pdf_url":"https://www.mdpi.com/2072-4292/11/24/2912/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/2072-4292/11/24/2912/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100611551","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0001-8808-7961"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Liu","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]},{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046974812","display_name":"Mengyuan Yang","orcid":"https://orcid.org/0000-0003-3418-711X"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"MengYuan Yang","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100590102","display_name":"Meng Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Xie","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112866399","display_name":"Zihui Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihui Guo","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088082868","display_name":"ErZhu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ErZhu Li","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101612318","display_name":"Lianpeng Zhang","orcid":"https://orcid.org/0000-0001-9765-9730"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianpeng Zhang","raw_affiliation_strings":["School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China"],"affiliations":[{"raw_affiliation_string":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xu Zhou 221116, China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042431974","display_name":"Tao Pei","orcid":"https://orcid.org/0000-0002-5311-8761"},"institutions":[{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Pei","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391508","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0002-8139-8502"},"institutions":[{"id":"https://openalex.org/I4210119683","display_name":"Zhejiang Water Conservancy and Hydropower Survey and Design Institute","ror":"https://ror.org/02n6dhr29","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210119683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Zhejiang Design Institute of Water Conservancy & Hydro-electric Power, Hangzhou 310002, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Design Institute of Water Conservancy & Hydro-electric Power, Hangzhou 310002, China","institution_ids":["https://openalex.org/I4210119683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100611551"],"corresponding_institution_ids":["https://openalex.org/I118574674","https://openalex.org/I4210160793"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.2884,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.86832846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"24","first_page":"2912","last_page":"2912"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/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":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7789222002029419},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6224942803382874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5641547441482544},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5614543557167053},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4769153296947479},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.46265938878059387},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4448097050189972},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43341535329818726},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37435996532440186},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32088345289230347},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15052542090415955}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7789222002029419},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6224942803382874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5641547441482544},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5614543557167053},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4769153296947479},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.46265938878059387},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4448097050189972},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43341535329818726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37435996532440186},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32088345289230347},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15052542090415955},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs11242912","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11242912","pdf_url":"https://www.mdpi.com/2072-4292/11/24/2912/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:mdpi.com:/2072-4292/11/24/2912/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11242912","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11242912","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11242912","pdf_url":"https://www.mdpi.com/2072-4292/11/24/2912/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":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1007721318","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320327518","funder_display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions"},{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1975743441","display_name":null,"funder_award_id":"2018054","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2071443865","display_name":null,"funder_award_id":"201805","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2423247345","display_name":null,"funder_award_id":"41525004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G352065052","display_name":null,"funder_award_id":"none","funder_id":"https://openalex.org/F4320326832","funder_display_name":"State Key Laboratory of Resources and Environmental Information System"},{"id":"https://openalex.org/G3744313044","display_name":null,"funder_award_id":"Social","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3935756157","display_name":null,"funder_award_id":"142100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5213207277","display_name":null,"funder_award_id":"41601405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5311346577","display_name":null,"funder_award_id":"2018001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6352588581","display_name":null,"funder_award_id":"41421001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7342455266","display_name":null,"funder_award_id":"(PAPD)","funder_id":"https://openalex.org/F4320327518","funder_display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions"},{"id":"https://openalex.org/G8563196907","display_name":null,"funder_award_id":"none","funder_id":"https://openalex.org/F4320327518","funder_display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions"},{"id":"https://openalex.org/G8943248878","display_name":null,"funder_award_id":"41590845","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/F4320326832","display_name":"State Key Laboratory of Resources and Environmental Information System","ror":null},{"id":"https://openalex.org/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2993017798.pdf","grobid_xml":"https://content.openalex.org/works/W2993017798.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W73112891","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1970455792","https://openalex.org/W1974981350","https://openalex.org/W1986856385","https://openalex.org/W2000829045","https://openalex.org/W2020131061","https://openalex.org/W2028104478","https://openalex.org/W2047662161","https://openalex.org/W2085625911","https://openalex.org/W2148868685","https://openalex.org/W2164976328","https://openalex.org/W2297575004","https://openalex.org/W2308318555","https://openalex.org/W2339884362","https://openalex.org/W2362565039","https://openalex.org/W2494341560","https://openalex.org/W2520578523","https://openalex.org/W2523500206","https://openalex.org/W2546092183","https://openalex.org/W2563705555","https://openalex.org/W2609077090","https://openalex.org/W2619037961","https://openalex.org/W2623490820","https://openalex.org/W2685970220","https://openalex.org/W2737129951","https://openalex.org/W2750722971","https://openalex.org/W2755304890","https://openalex.org/W2760340275","https://openalex.org/W2778539913","https://openalex.org/W2787614951","https://openalex.org/W2797789005","https://openalex.org/W2800388963","https://openalex.org/W2804860796","https://openalex.org/W2810004461","https://openalex.org/W2885628263","https://openalex.org/W2894660140","https://openalex.org/W2897992168","https://openalex.org/W2903282641","https://openalex.org/W2907459272","https://openalex.org/W2908828809","https://openalex.org/W2924260171","https://openalex.org/W2930359273","https://openalex.org/W2949930576","https://openalex.org/W2963659230","https://openalex.org/W2963881378","https://openalex.org/W2966450079","https://openalex.org/W2990136631","https://openalex.org/W2996355131","https://openalex.org/W3100521496","https://openalex.org/W3105127913","https://openalex.org/W6646800459","https://openalex.org/W6655359414","https://openalex.org/W6772101785"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4225147082","https://openalex.org/W2778653980"],"abstract_inverted_index":{"Accurate":[0],"extraction":[1,56,78,105,192,202,243],"of":[2,15,29,57,79,97,125,193,200,203,219,253,263,289],"buildings":[3,58,134,307],"using":[4],"high":[5,158],"spatial":[6,159],"resolution":[7,160],"imagery":[8],"is":[9,20,59,106,187,209,214],"essential":[10],"to":[11,22,84,87,92,131,140],"a":[12,27,148,206,220],"wide":[13],"range":[14],"urban":[16,34,36,80,237,272,298],"applications.":[17],"However,":[18,108],"it":[19],"difficult":[21],"extract":[23,132,306],"semantic":[24],"features":[25,90,176],"from":[26,179],"variety":[28],"complex":[30,41],"scenes":[31],"(e.g.,":[32],"suburban,":[33,234,269,295],"and":[35,50,91,114,128,135,166,183,227,236,256,258,266,271,284,292,297,311,314],"village":[37,273,299],"areas)":[38],"because":[39],"various":[40],"man-made":[42,81],"objects":[43,82],"usually":[44],"appear":[45],"heterogeneous":[46],"with":[47,281,308,312],"large":[48],"intra-class":[49],"low":[51],"inter-class":[52],"variations.":[53],"The":[54,63,245,302],"automatic":[55],"thus":[60],"extremely":[61],"challenging.":[62],"fully":[64,151],"convolutional":[65,152],"neural":[66,153],"networks":[67],"(FCNs)":[68],"developed":[69],"in":[70,76,103,119,268,279,287,294],"recent":[71],"years":[72],"have":[73],"performed":[74],"well":[75],"the":[77,98,109,123,129,167,180,190,194,198,217,249,277,282],"due":[83],"their":[85],"ability":[86,130],"learn":[88],"state-of-the-art":[89],"label":[93],"pixels":[94],"end-to-end.":[95],"One":[96],"most":[99],"successful":[100],"FCNs":[101],"used":[102,111,188,215],"building":[104,137,173,204,222,242],"U-net.":[107],"commonly":[110],"skip":[112],"connection":[113],"feature":[115,126],"fusion":[116,181],"refinement":[117],"modules":[118],"U-net":[120,186,207,285],"often":[121],"ignore":[122],"problem":[124,199],"selection,":[127],"smaller":[133],"refine":[136],"boundaries":[138],"needs":[139],"be":[141],"improved.":[142],"In":[143],"this":[144],"paper,":[145],"we":[146],"propose":[147],"trainable":[149],"chain":[150],"network":[154,208],"(CFCN),":[155],"which":[156,213],"fuses":[157],"unmanned":[161],"aerial":[162],"vehicle":[163],"(UAV)":[164],"images":[165],"digital":[168],"surface":[169],"model":[170],"(DSM)":[171],"for":[172,189,216,241],"extraction.":[174],"Multilevel":[175],"are":[177],"obtained":[178],"data,":[182],"an":[184],"improved":[185],"coarse":[191,221],"building.":[195],"To":[196],"solve":[197],"incomplete":[201],"boundaries,":[205],"introduced":[210],"by":[211],"chain,":[212],"introduction":[218],"boundary":[223],"constraint,":[224],"hole":[225],"filling,":[226],"\"speckle\"":[228],"removal.":[229],"Typical":[230],"areas":[231],"such":[232],"as":[233],"urban,":[235,270,296],"villages":[238],"were":[239],"selected":[240],"experiments.":[244],"results":[246],"show":[247],"that":[248],"CFCN":[250,283],"achieved":[251],"recall":[252],"98.67%,":[254],"98.62%,":[255],"99.52%":[257],"intersection":[259],"over":[260],"union":[261],"(IoU)":[262],"96.23%,":[264],"96.43%,":[265],"95.76%":[267],"areas,":[274,300],"respectively.":[275,301],"Considering":[276],"IoU":[278],"conjunction":[280],"resulted":[286],"improvements":[288],"6.61%,":[290],"5.31%,":[291],"6.45%":[293],"proposed":[303],"method":[304],"can":[305],"higher":[309],"accuracy":[310],"clearer":[313],"more":[315],"complete":[316],"boundaries.":[317]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}