{"id":"https://openalex.org/W2584768951","doi":"https://doi.org/10.1109/bigdata.2016.7840915","title":"Large-scale solar panel mapping from aerial images using deep convolutional networks","display_name":"Large-scale solar panel mapping from aerial images using deep convolutional networks","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2584768951","doi":"https://doi.org/10.1109/bigdata.2016.7840915","mag":"2584768951"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7840915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","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":"https://openalex.org/A5101743528","display_name":"Jiangye Yuan","orcid":"https://orcid.org/0000-0001-8551-9925"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiangye Yuan","raw_affiliation_strings":["Oak Ridge National Laboratory, Oak Ridge, Tennessee"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, Tennessee","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024089585","display_name":"H. Lexie Yang","orcid":"https://orcid.org/0000-0003-2252-6778"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsiu-Han Lexie Yang","raw_affiliation_strings":["Oak Ridge National Laboratory, Oak Ridge, Tennessee"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, Tennessee","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066113226","display_name":"Olufemi A. Omitaomu","orcid":"https://orcid.org/0000-0002-3078-7196"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olufemi A. Omitaomu","raw_affiliation_strings":["Oak Ridge National Laboratory, Oak Ridge, Tennessee"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, Tennessee","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104505028","display_name":"Budhendra Bhaduri","orcid":"https://orcid.org/0000-0003-1555-1377"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Budhendra L. Bhaduri","raw_affiliation_strings":["Oak Ridge National Laboratory, Oak Ridge, Tennessee"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, Tennessee","institution_ids":["https://openalex.org/I1289243028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101743528"],"corresponding_institution_ids":["https://openalex.org/I1289243028"],"apc_list":null,"apc_paid":null,"fwci":1.3355,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.79769216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2703","last_page":"2708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11336","display_name":"Energy and Environment Impacts","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T11336","display_name":"Energy and Environment Impacts","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6885982751846313},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6715656518936157},{"id":"https://openalex.org/keywords/photovoltaic-system","display_name":"Photovoltaic system","score":0.6099360585212708},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5972106456756592},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.5730758309364319},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5260239243507385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5019545555114746},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.47540292143821716},{"id":"https://openalex.org/keywords/aerial-photography","display_name":"Aerial photography","score":0.42602843046188354},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4203316569328308},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4153035879135132},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.247866690158844},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22213277220726013},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14386072754859924},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13386684656143188},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12259268760681152},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10181501507759094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6885982751846313},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6715656518936157},{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.6099360585212708},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5972106456756592},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.5730758309364319},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5260239243507385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5019545555114746},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.47540292143821716},{"id":"https://openalex.org/C133214962","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial photography","level":2,"score":0.42602843046188354},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4203316569328308},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4153035879135132},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.247866690158844},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22213277220726013},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14386072754859924},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13386684656143188},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12259268760681152},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10181501507759094},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2016.7840915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1606347560","https://openalex.org/W1903029394","https://openalex.org/W1908321067","https://openalex.org/W2156727185","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2277790332","https://openalex.org/W2406907097","https://openalex.org/W2919115771","https://openalex.org/W2963542991","https://openalex.org/W6629368666","https://openalex.org/W6636358008","https://openalex.org/W6684191040","https://openalex.org/W6695039437"],"related_works":["https://openalex.org/W2372478594","https://openalex.org/W2652346890","https://openalex.org/W3205848368","https://openalex.org/W2975420069","https://openalex.org/W4283696875","https://openalex.org/W2976105433","https://openalex.org/W3110585990","https://openalex.org/W4251840164","https://openalex.org/W4385767632","https://openalex.org/W2386046054"],"abstract_inverted_index":{"Up-to-date":[0],"maps":[1,22],"of":[2,16,105,128],"installed":[3],"solar":[4,17,48,78,89],"photovoltaic":[5],"panels":[6,49,79,90],"are":[7,26,53,109,113],"a":[8,65],"critical":[9],"input":[10],"for":[11,23],"policy":[12],"and":[13,32,126],"financial":[14],"assessment":[15],"distributed":[18],"generation.":[19],"However,":[20],"such":[21],"large":[24],"areas":[25],"not":[27],"available.":[28],"With":[29],"high":[30],"coverage":[31],"low":[33],"cost,":[34],"aerial":[35,81],"images":[36],"enable":[37],"large-scale":[38],"mapping,":[39,122],"but":[40],"it":[41],"is":[42,85],"highly":[43],"difficult":[44],"to":[45,76,87,120],"automatically":[46],"identify":[47],"from":[50],"images,":[51],"which":[52,73],"small":[54],"objects":[55],"with":[56,116],"varying":[57],"appearances":[58],"dispersed":[59],"in":[60,80,91,97],"complex":[61],"scenes.":[62,82],"We":[63],"introduce":[64],"new":[66],"approach":[67,84],"based":[68],"on":[69],"deep":[70],"convolutional":[71],"networks,":[72],"effectively":[74],"learns":[75],"delineate":[77],"The":[83],"applied":[86],"mapping":[88],"imagery":[92],"covering":[93],"200":[94],"square":[95,103],"kilometers":[96,104],"two":[98],"cities,":[99],"using":[100],"only":[101],"12":[102],"training":[106],"data":[107],"that":[108],"manually":[110],"labeled.":[111],"Results":[112],"generated":[114],"efficiently":[115],"an":[117],"accuracy":[118],"comparable":[119],"manual":[121],"demonstrating":[123],"the":[124],"effectiveness":[125],"scalability":[127],"our":[129],"approach.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-10-10T00:00:00"}