{"id":"https://openalex.org/W3129525896","doi":"https://doi.org/10.1109/igarss39084.2020.9323541","title":"Accurate Detection of Historical Buildings Using Aerial Photographs and Deep Transfer Learning","display_name":"Accurate Detection of Historical Buildings Using Aerial Photographs and Deep Transfer Learning","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3129525896","doi":"https://doi.org/10.1109/igarss39084.2020.9323541","mag":"3129525896"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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":null,"display_name":"Yongzhu Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I160391749","display_name":"Jiaying University","ror":"https://ror.org/018jdfk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I160391749"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongzhu Xiong","raw_affiliation_strings":["School of Geography and Tourism, Jiaying University,Meizhou,China,514015"],"affiliations":[{"raw_affiliation_string":"School of Geography and Tourism, Jiaying University,Meizhou,China,514015","institution_ids":["https://openalex.org/I160391749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003673355","display_name":"Qi Chen","orcid":"https://orcid.org/0000-0003-0110-7996"},"institutions":[{"id":"https://openalex.org/I117965899","display_name":"University of Hawai\u02bbi at M\u0101noa","ror":"https://ror.org/01wspgy28","country_code":"US","type":"education","lineage":["https://openalex.org/I117965899"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Chen","raw_affiliation_strings":["University of Hawai'i at M\u0101noa,Department of Geography and Environment,Honolulu,USA,96822"],"affiliations":[{"raw_affiliation_string":"University of Hawai'i at M\u0101noa,Department of Geography and Environment,Honolulu,USA,96822","institution_ids":["https://openalex.org/I117965899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078408683","display_name":"Mingyong Zhu","orcid":"https://orcid.org/0000-0001-6849-1692"},"institutions":[{"id":"https://openalex.org/I160391749","display_name":"Jiaying University","ror":"https://ror.org/018jdfk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I160391749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyong Zhu","raw_affiliation_strings":["School of Geography and Tourism, Jiaying University,Meizhou,China,514015"],"affiliations":[{"raw_affiliation_string":"School of Geography and Tourism, Jiaying University,Meizhou,China,514015","institution_ids":["https://openalex.org/I160391749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733296","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0002-0043-4904"},"institutions":[{"id":"https://openalex.org/I160391749","display_name":"Jiaying University","ror":"https://ror.org/018jdfk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I160391749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["School of Geography and Tourism, Jiaying University,Meizhou,China,514015"],"affiliations":[{"raw_affiliation_string":"School of Geography and Tourism, Jiaying University,Meizhou,China,514015","institution_ids":["https://openalex.org/I160391749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029292003","display_name":"Ke-Kun Huang","orcid":"https://orcid.org/0000-0002-0163-4182"},"institutions":[{"id":"https://openalex.org/I160391749","display_name":"Jiaying University","ror":"https://ror.org/018jdfk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I160391749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kekun Huang","raw_affiliation_strings":["School of Mathematics, Jiaying University,Meizhou,China,514015"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, Jiaying University,Meizhou,China,514015","institution_ids":["https://openalex.org/I160391749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I160391749"],"apc_list":null,"apc_paid":null,"fwci":5.0418,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94818653,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1592","last_page":"1595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12364","display_name":"Archaeological Research and Protection","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1912","display_name":"Space and Planetary Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12364","display_name":"Archaeological Research and Protection","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1912","display_name":"Space and Planetary Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983999729156494,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9830999970436096,"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/transfer-of-learning","display_name":"Transfer of learning","score":0.7596555948257446},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.7426638603210449},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6848832368850708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6759667992591858},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.6721188426017761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097404360771179},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5660709738731384},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.5151599645614624},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4707620441913605},{"id":"https://openalex.org/keywords/residence","display_name":"Residence","score":0.46546199917793274},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41978687047958374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39895331859588623},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.395624577999115},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3432731628417969},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.20334655046463013},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.20247289538383484},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1805441975593567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14952346682548523},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.0856473445892334}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7596555948257446},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.7426638603210449},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6848832368850708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6759667992591858},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.6721188426017761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097404360771179},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5660709738731384},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.5151599645614624},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4707620441913605},{"id":"https://openalex.org/C2776269092","wikidata":"https://www.wikidata.org/wiki/Q1611074","display_name":"Residence","level":2,"score":0.46546199917793274},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41978687047958374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39895331859588623},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.395624577999115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3432731628417969},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.20334655046463013},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.20247289538383484},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1805441975593567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14952346682548523},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0856473445892334},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3810932006","display_name":null,"funder_award_id":"61976104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7929405184","display_name":null,"funder_award_id":"2017A030307040","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8495767161","display_name":null,"funder_award_id":"201808440171","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2028104478","https://openalex.org/W2029316659","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2308318555","https://openalex.org/W2412588858","https://openalex.org/W2565950292","https://openalex.org/W2618530766","https://openalex.org/W2764034829","https://openalex.org/W2782522152","https://openalex.org/W2790979755","https://openalex.org/W2792165427","https://openalex.org/W2801305081","https://openalex.org/W2804532080","https://openalex.org/W2899101283","https://openalex.org/W2901712839","https://openalex.org/W2908320224","https://openalex.org/W2920641855","https://openalex.org/W2940726923","https://openalex.org/W2944516111","https://openalex.org/W2945385604","https://openalex.org/W2950476788","https://openalex.org/W3105946634","https://openalex.org/W6749467398","https://openalex.org/W6967303126"],"related_works":["https://openalex.org/W4283696875","https://openalex.org/W3110585990","https://openalex.org/W4385767632","https://openalex.org/W2889866244","https://openalex.org/W2898690910","https://openalex.org/W2784132289","https://openalex.org/W4286697184","https://openalex.org/W2889700547","https://openalex.org/W3034139063","https://openalex.org/W2593313455"],"abstract_inverted_index":{"Deep":[0],"learning":[1,37,192],"(DL)":[2],"has":[3,170],"increasingly":[4],"witnessed":[5],"a":[6,33,50,63,111,128,171,197],"lot":[7],"of":[8,53,61,87,113],"applications":[9],"and":[10,56,90,107,124,155,174,207],"advancements":[11],"in":[12,27,209],"remote":[13],"sensing":[14],"(RS).":[15],"However,":[16],"it":[17,21],"remains":[18],"unclear":[19],"whether":[20],"can":[22,193],"accurately":[23,206],"detect":[24,45,203],"historical":[25,54,204],"buildings":[26,205],"RS":[28,71,200],"imagery.":[29],"Here":[30],"we":[31],"proposed":[32],"new":[34,198],"deep":[35,190],"transfer":[36,122,191],"approach":[38,116],"based":[39],"on":[40],"aerial":[41,85,210],"photographs":[42,86],"to":[43,202],"automatically":[44],"Hakka":[46,75,98],"Weilong":[47,76],"Houses":[48],"(HWHs),":[49],"famous":[51],"type":[52],"residence":[55],"an":[57,175],"important":[58],"cultural":[59],"symbol":[60],"Hakka,":[62],"Han":[64],"Chinese":[65],"subgroup":[66],"across":[67],"the":[68,88,96,120,135,140,145,156,179],"world.":[69],"An":[70],"image":[72,161],"dataset,":[73],"namely":[74],"House":[77],"Image":[78],"Dataset":[79],"(HWHID),":[80],"was":[81,102,138,143,153,163],"created":[82],"by":[83],"using":[84],"urban":[89],"suburban":[91],"Meizhou,":[92],"which":[93],"is":[94],"called":[95],"world":[97],"capital.":[99],"The":[100],"dataset":[101],"randomly":[103],"shuffled":[104],"into":[105],"training":[106,129,152],"testing":[108],"ones":[109],"with":[110],"ratio":[112],"8:2.":[114],"Our":[115,183],"used":[117,195],"ResNet50":[118],"as":[119,127,196],"backbone":[121],"network":[123],"YOLO":[125],"v2":[126],"framework.":[130],"Experimental":[131],"results":[132],"showed":[133],"that":[134,167,188],"average":[136,157],"precision":[137],"0.9599\u00b10.0150,":[139],"loss":[141],"rate":[142],"0.0250,":[144],"Root":[146],"Mean":[147],"Square":[148],"Error":[149],"(RMSE)":[150],"for":[151,178],"0.1580,":[154],"detecting":[158],"time":[159],"per":[160],"clip":[162],"0.0383\u00b10.0150":[164],"second,":[165],"suggesting":[166],"our":[168],"model":[169],"high":[172],"accuracy":[173],"excellent":[176],"performance":[177],"HWH":[180],"detection":[181],"task.":[182],"findings":[184],"provide":[185],"concrete":[186],"evidences":[187],"aerial-imagery-based":[189],"be":[194],"archaeological":[199],"method":[201],"rapidly":[208],"photographs.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
