{"id":"https://openalex.org/W2890554472","doi":"https://doi.org/10.1109/jstars.2018.2866284","title":"Multilevel Building Detection Framework in Remote Sensing Images Based on Convolutional Neural Networks","display_name":"Multilevel Building Detection Framework in Remote Sensing Images Based on Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-09-21","ids":{"openalex":"https://openalex.org/W2890554472","doi":"https://doi.org/10.1109/jstars.2018.2866284","mag":"2890554472"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2866284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2866284","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5100656709","display_name":"Yibo Liu","orcid":"https://orcid.org/0000-0002-3168-0630"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Liu","raw_affiliation_strings":["Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3168-0630","affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101584424","display_name":"Zhenxin Zhang","orcid":"https://orcid.org/0000-0002-4070-9415"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxin Zhang","raw_affiliation_strings":["Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4070-9415","affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039088967","display_name":"Ruofei Zhong","orcid":"https://orcid.org/0000-0002-6064-4479"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruofei Zhong","raw_affiliation_strings":["Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013116360","display_name":"Dong Chen","orcid":"https://orcid.org/0000-0001-8118-3889"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Chen","raw_affiliation_strings":["College of Civil Engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8118-3889","affiliations":[{"raw_affiliation_string":"College of Civil Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089180563","display_name":"Yinghai Ke","orcid":"https://orcid.org/0000-0002-1121-1378"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghai Ke","raw_affiliation_strings":["Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027174277","display_name":"Jiju Peethambaran","orcid":"https://orcid.org/0000-0003-0245-5933"},"institutions":[{"id":"https://openalex.org/I66890659","display_name":"Saint Mary's University","ror":"https://ror.org/010zh7098","country_code":"CA","type":"education","lineage":["https://openalex.org/I66890659"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiju Peethambaran","raw_affiliation_strings":["Department of Mathematics and Computing, Saint Mary's University, Halifax, NS, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0245-5933","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computing, Saint Mary's University, Halifax, NS, Canada","institution_ids":["https://openalex.org/I66890659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088401193","display_name":"Chuqun Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101167","display_name":"Institute of Oceanology","ror":"https://ror.org/018yw5541","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210101167"]},{"id":"https://openalex.org/I4210103685","display_name":"South China Sea Institute Of Oceanology","ror":"https://ror.org/0192yj155","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210103685"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuqun Chen","raw_affiliation_strings":["Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology Chinese Academy of Sciences, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology Chinese Academy of Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210101167","https://openalex.org/I4210103685"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101534247","display_name":"Lan Sun","orcid":"https://orcid.org/0000-0002-9527-7680"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Sun","raw_affiliation_strings":["Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":null,"fwci":4.3805,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.94492532,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":"10","first_page":"3688","last_page":"3700"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7648317217826843},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7587978839874268},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6580018997192383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6279188990592957},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6074685454368591},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.573901355266571},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5305873155593872},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4821612238883972},{"id":"https://openalex.org/keywords/building-model","display_name":"Building model","score":0.4781685471534729},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44864165782928467},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3697708249092102},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10794967412948608},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.07519251108169556}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7648317217826843},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7587978839874268},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6580018997192383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6279188990592957},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6074685454368591},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.573901355266571},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5305873155593872},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4821612238883972},{"id":"https://openalex.org/C2778530916","wikidata":"https://www.wikidata.org/wiki/Q1352349","display_name":"Building model","level":2,"score":0.4781685471534729},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44864165782928467},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3697708249092102},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10794967412948608},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.07519251108169556},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2018.2866284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2866284","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G251742388","display_name":null,"funder_award_id":"41301521","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3879756750","display_name":null,"funder_award_id":"41701533","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8730668557","display_name":"\u57fa\u4e8e\u7ed3\u6784\u7279\u5f81\u7684\u8f66\u8f7d\u6fc0\u5149\u626b\u63cf\u7cfb\u7edf\u5916\u65b9\u4f4d\u5143\u7d20\u5728\u7ebf\u6807\u5b9a\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41371434","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1526295910","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1966178163","https://openalex.org/W1974981350","https://openalex.org/W2006623133","https://openalex.org/W2012273471","https://openalex.org/W2020719522","https://openalex.org/W2022508996","https://openalex.org/W2023939759","https://openalex.org/W2027282554","https://openalex.org/W2028104478","https://openalex.org/W2037143195","https://openalex.org/W2049677900","https://openalex.org/W2069677644","https://openalex.org/W2081865073","https://openalex.org/W2085625911","https://openalex.org/W2085665642","https://openalex.org/W2086355237","https://openalex.org/W2091206906","https://openalex.org/W2097117768","https://openalex.org/W2098676252","https://openalex.org/W2100002341","https://openalex.org/W2102605133","https://openalex.org/W2105032938","https://openalex.org/W2109255472","https://openalex.org/W2120832559","https://openalex.org/W2126527280","https://openalex.org/W2145717442","https://openalex.org/W2152449524","https://openalex.org/W2155893237","https://openalex.org/W2157284958","https://openalex.org/W2163605009","https://openalex.org/W2166424889","https://openalex.org/W2168356304","https://openalex.org/W2183182206","https://openalex.org/W2194600502","https://openalex.org/W2194775991","https://openalex.org/W2238499080","https://openalex.org/W2308318555","https://openalex.org/W2330711204","https://openalex.org/W2340624627","https://openalex.org/W2471353525","https://openalex.org/W2503140068","https://openalex.org/W2512351403","https://openalex.org/W2513955405","https://openalex.org/W2539889958","https://openalex.org/W2548528364","https://openalex.org/W2560167313","https://openalex.org/W2565639579","https://openalex.org/W2577537809","https://openalex.org/W2609402060","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2770844153","https://openalex.org/W2963037989","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639204139","https://openalex.org/W6674813771","https://openalex.org/W6675126961"],"related_works":["https://openalex.org/W4249847449","https://openalex.org/W44395729","https://openalex.org/W4321487865","https://openalex.org/W2765338038","https://openalex.org/W1496225612","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"In":[0],"this":[1,26],"paper,":[2],"we":[3,28,87],"propose":[4],"a":[5],"hierarchical":[6],"building":[7,49,59,70,78,85,91,108,164],"detection":[8,92,137,165],"framework":[9,156],"based":[10],"on":[11,17,82],"deep":[12],"learning":[13],"model,":[14,124],"which":[15,101],"focuses":[16],"accurately":[18],"detecting":[19],"buildings":[20,187],"from":[21,100],"remote":[22],"sensing":[23],"images.":[24],"To":[25],"end,":[27],"first":[29],"construct":[30],"the":[31,35,40,46,58,74,77,83,89,95,102,114,126,136,144,154,158,173,180,186],"generation":[32],"model":[33,93,128],"of":[34,48,76,106,138,163],"multilevel":[36,90],"training":[37,122],"samples":[38],"using":[39,94,143],"Gaussian":[41],"pyramid":[42],"technique":[43],"to":[44,66,132,185],"learn":[45],"features":[47,105,116],"objects":[50],"at":[51],"different":[52,189],"scales":[53],"and":[54,125,147,169,192],"spatial":[55,190],"resolutions.":[56],"Then,":[57],"region":[60,109],"proposal":[61,110],"networks":[62,98],"are":[63,111,117],"put":[64],"forward":[65],"quickly":[67],"extract":[68],"candidate":[69,84],"regions,":[71,86],"thereby":[72],"increasing":[73],"efficiency":[75],"object":[79],"detection.":[80],"Based":[81],"establish":[88],"convolutional":[96],"neural":[97],"(CNNs),":[99],"generic":[103],"image":[104],"each":[107],"calculated.":[112],"Finally,":[113],"obtained":[115],"provided":[118],"as":[119],"inputs":[120],"for":[121,135],"CNNs":[123],"learned":[127],"is":[129,183],"further":[130],"applied":[131],"test":[133],"images":[134],"unknown":[139],"buildings.":[140],"Various":[141],"experiments":[142],"Datasets":[145],"I":[146],"II":[148],"(in":[149],"Section":[150],"V-A)":[151],"show":[152],"that":[153],"proposed":[155,181],"increases":[157],"mean":[159],"average":[160],"precision":[161],"values":[162],"by":[166],"3.63%,":[167],"3.85%,":[168],"3.77%,":[170],"compared":[171],"with":[172],"state-of-the-art":[174],"methods,":[175],"i.e.,":[176],"Method":[177],"IV.":[178],"Besides,":[179],"method":[182],"robust":[184],"having":[188],"textures":[191],"types.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}