{"id":"https://openalex.org/W4313546603","doi":"https://doi.org/10.1109/jstars.2022.3229460","title":"LRAD-Net: An Improved Lightweight Network for Building Extraction From Remote Sensing Images","display_name":"LRAD-Net: An Improved Lightweight Network for Building Extraction From Remote Sensing Images","publication_year":2022,"publication_date":"2022-12-15","ids":{"openalex":"https://openalex.org/W4313546603","doi":"https://doi.org/10.1109/jstars.2022.3229460"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3229460","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3229460","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09987671.pdf","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09987671.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043321452","display_name":"Jiabin Liu","orcid":"https://orcid.org/0000-0002-7730-5967"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiabin Liu","raw_affiliation_strings":["School of Geographic Science and Remote Sensing, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Geographic Science and Remote Sensing, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084376897","display_name":"Huaigang Huang","orcid":"https://orcid.org/0000-0002-8804-6390"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Huaigang Huang","raw_affiliation_strings":["Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100529353","display_name":"Hanxiao Sun","orcid":"https://orcid.org/0009-0006-4108-517X"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanxiao Sun","raw_affiliation_strings":["School of Geographic Science and Remote Sensing, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Geographic Science and Remote Sensing, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101463975","display_name":"Zhifeng Wu","orcid":"https://orcid.org/0000-0003-3173-4739"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifeng Wu","raw_affiliation_strings":["School of Geography and Remote Sensing, and MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Guangzhou University, Guangzhou, China","Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Remote Sensing, and MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]},{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China","institution_ids":["https://openalex.org/I4210106122"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079715088","display_name":"Renbo Luo","orcid":"https://orcid.org/0000-0002-4262-5506"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I4210132195","display_name":"Guangdong Province Environmental Monitoring Center","ror":"https://ror.org/03gfeke93","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132195"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renbo Luo","raw_affiliation_strings":["School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China","Guangdong Province Engineering Technology Research Center for Geographical Conditions Monitoring and Comprehensive Analysis, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]},{"raw_affiliation_string":"Guangdong Province Engineering Technology Research Center for Geographical Conditions Monitoring and Comprehensive Analysis, Guangzhou, China","institution_ids":["https://openalex.org/I4210132195"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043321452"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":2.3483,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90135209,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"16","issue":null,"first_page":"675","last_page":"687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994999766349792,"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":0.9993000030517578,"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":0.8229143619537354},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.66056227684021},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6281644105911255},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5701714754104614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5630605220794678},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5630316734313965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4972436726093292},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4852025806903839},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4769015312194824},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4622148871421814},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.46067437529563904},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4356600046157837},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41506972908973694},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.40073105692863464},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3386901021003723},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2187407910823822},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1343407928943634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8229143619537354},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.66056227684021},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6281644105911255},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5701714754104614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5630605220794678},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5630316734313965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4972436726093292},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4852025806903839},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4769015312194824},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4622148871421814},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.46067437529563904},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4356600046157837},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41506972908973694},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.40073105692863464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3386901021003723},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2187407910823822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1343407928943634},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2022.3229460","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3229460","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09987671.pdf","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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"},{"id":"pmh:oai:doaj.org/article:7ce07c41b79d441fa8529b0a47319773","is_oa":true,"landing_page_url":"https://doaj.org/article/7ce07c41b79d441fa8529b0a47319773","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 675-687 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3229460","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3229460","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09987671.pdf","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":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1477544716","display_name":null,"funder_award_id":"Guangdong","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1749516439","display_name":null,"funder_award_id":"2018B03031200","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"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/G2441240401","display_name":null,"funder_award_id":"2018B030312004","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"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/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5452762153","display_name":null,"funder_award_id":"2018B030312","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","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/G8717829035","display_name":null,"funder_award_id":"41801250","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/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313546603.pdf","grobid_xml":"https://content.openalex.org/works/W4313546603.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W1579869106","https://openalex.org/W1650736245","https://openalex.org/W1901129140","https://openalex.org/W1923697677","https://openalex.org/W2001510610","https://openalex.org/W2017339910","https://openalex.org/W2022508996","https://openalex.org/W2044015570","https://openalex.org/W2069880880","https://openalex.org/W2109255472","https://openalex.org/W2141573384","https://openalex.org/W2171713125","https://openalex.org/W2185464637","https://openalex.org/W2197852308","https://openalex.org/W2291193232","https://openalex.org/W2338652272","https://openalex.org/W2395611524","https://openalex.org/W2404464147","https://openalex.org/W2412782625","https://openalex.org/W2496759915","https://openalex.org/W2531409750","https://openalex.org/W2560023338","https://openalex.org/W2608096492","https://openalex.org/W2609402060","https://openalex.org/W2618530766","https://openalex.org/W2630837129","https://openalex.org/W2752782242","https://openalex.org/W2776462702","https://openalex.org/W2787091153","https://openalex.org/W2790741584","https://openalex.org/W2884436604","https://openalex.org/W2884585870","https://openalex.org/W2886934227","https://openalex.org/W2900094710","https://openalex.org/W2902036000","https://openalex.org/W2927945203","https://openalex.org/W2946547492","https://openalex.org/W2963125010","https://openalex.org/W2963881378","https://openalex.org/W2963918968","https://openalex.org/W2964304707","https://openalex.org/W2979428117","https://openalex.org/W2982083293","https://openalex.org/W2982206001","https://openalex.org/W2997225633","https://openalex.org/W3004265084","https://openalex.org/W3015788359","https://openalex.org/W3022397457","https://openalex.org/W3034429256","https://openalex.org/W3034552520","https://openalex.org/W3104035745","https://openalex.org/W3122259118","https://openalex.org/W3148283428","https://openalex.org/W3156066202","https://openalex.org/W3181955139","https://openalex.org/W3196904463","https://openalex.org/W3215100961","https://openalex.org/W4297775537","https://openalex.org/W6637078681","https://openalex.org/W6640054144","https://openalex.org/W6686235763","https://openalex.org/W6737664043","https://openalex.org/W6739696289","https://openalex.org/W6751733626","https://openalex.org/W6762718338","https://openalex.org/W6798274885"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758","https://openalex.org/W4320059067","https://openalex.org/W4281729897"],"abstract_inverted_index":{"The":[0],"building":[1,68,206,286],"extraction":[2,69,104,287],"method":[3],"of":[4,17,23,50,109,131,167,189,198,204,216,260,266,280],"remote":[5,71],"sensing":[6,72],"images":[7],"that":[8],"uses":[9],"deep":[10],"learning":[11],"algorithms":[12],"can":[13,36,75,160,182,256,275],"solve":[14],"the":[15,85,88,134,137,146,162,168,187,202,212,239,245,277,281,285],"problems":[16],"low":[18],"efficiency":[19],"and":[20,47,82,128,156,164,191,200,214,230,244,262,289],"poor":[21],"effect":[22,288],"traditional":[24],"methods":[25],"during":[26],"feature":[27,103,151],"extraction.":[28],"Although":[29],"some":[30],"semantic":[31],"segmentation":[32,39],"networks":[33],"proposed":[34,123,217],"recently":[35],"achieve":[37],"good":[38],"performance":[40],"in":[41,56],"extracting":[42],"buildings,":[43],"their":[44],"huge":[45],"parameters":[46],"large":[48],"amount":[49],"calculation":[51],"lead":[52],"to":[53,124,144,210],"great":[54],"obstacles":[55],"practical":[57],"application.":[58],"Therefore,":[59],"we":[60,219],"propose":[61],"a":[62,113,172,195,223],"lightweight":[63,89,173],"network":[64,91,282],"(named":[65],"LRAD-Net)":[66],"for":[67],"from":[70,186],"images.":[73],"LRAD-Net":[74,255],"be":[76],"divided":[77],"into":[78],"two":[79],"stages:":[80],"encoding":[81,86],"decoding.":[83],"In":[84,133,208],"stage,":[87,136],"RegNet":[90],"with":[92,153,176,194,227,251],"600":[93],"million":[94],"flop":[95],"(600":[96],"MF)":[97],"is":[98,122,141,179],"finally":[99],"selected":[100],"as":[101],"our":[102],"backbone":[105],"net":[106],"though":[107],"lots":[108],"experimental":[110],"comparisons.":[111],"Then,":[112],"multiscale":[114],"depthwise":[115],"separable":[116],"atrous":[117],"spatial":[118],"pyramid":[119],"pooling":[120],"structure":[121],"extract":[125,257],"more":[126,258],"comprehensive":[127],"important":[129],"details":[130,155,259],"buildings.":[132,169],"decoding":[135],"squeeze-and-excitation":[138],"attention":[139],"mechanism":[140],"applied":[142],"innovatively":[143],"redistribute":[145],"channel":[147],"weights":[148],"before":[149],"fusing":[150],"maps":[152,190],"low-level":[154],"high-level":[157],"semantics,":[158],"thus":[159],"enrich":[161],"local":[163],"global":[165],"information":[166],"What's":[170],"more,":[171],"residual":[174],"block":[175],"polarized":[177],"self-attention":[178],"proposed,":[180],"it":[181],"incorporate":[183],"features":[184],"extracted":[185],"space":[188],"different":[192],"channels":[193],"small":[196],"number":[197,265],"parameters,":[199,267],"improve":[201,276],"accuracy":[203],"recovering":[205],"boundary.":[207],"order":[209],"verify":[211],"effectiveness":[213],"robustness":[215],"LRAD-Net,":[218],"conduct":[220],"experiments":[221],"on":[222],"self-annotated":[224],"UAV":[225],"dataset":[226,243],"higher":[228],"resolution":[229],"three":[231],"public":[232],"datasets":[233],"(the":[234],"WHU":[235,240],"aerial":[236,247],"image":[237,242,248],"dataset,":[238],"satellite":[241],"Inria":[246],"dataset).":[249],"Compared":[250],"several":[252],"representative":[253],"networks,":[254],"building,":[261],"has":[263],"smaller":[264],"faster":[268],"computing":[269],"speed,":[270],"stronger":[271],"generalization":[272],"ability,":[273],"which":[274],"training":[278],"speed":[279],"without":[283],"affecting":[284],"accuracy.":[290]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}