{"id":"https://openalex.org/W3132259895","doi":"https://doi.org/10.1109/igarss39084.2020.9323155","title":"A Novel Global-Aware Deep Network for Road Detection of Very High Resolution Remote Sensing Imagery","display_name":"A Novel Global-Aware Deep Network for Road Detection of Very High Resolution Remote Sensing Imagery","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3132259895","doi":"https://doi.org/10.1109/igarss39084.2020.9323155","mag":"3132259895"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323155","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":"conference-paper","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/A5011042925","display_name":"Xiaoyan Lu","orcid":"https://orcid.org/0000-0002-9026-8195"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Lu","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754351","display_name":"Yanfei Zhong","orcid":"https://orcid.org/0000-0001-9446-5850"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfei Zhong","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000877601","display_name":"Zhuo Zheng","orcid":"https://orcid.org/0000-0003-1811-6725"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Zheng","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0955,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76876972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2579","last_page":"2582"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9976999759674072,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9697999954223633,"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/computer-science","display_name":"Computer science","score":0.8104864358901978},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6410335898399353},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6014977693557739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.58992999792099},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5116177201271057},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5087860226631165},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.5082704424858093},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.4950057864189148},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4436284303665161},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4301508665084839},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4035278260707855},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3283386826515198},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11077553033828735},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10407039523124695},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06259354948997498}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8104864358901978},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6410335898399353},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6014977693557739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.58992999792099},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5116177201271057},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5087860226631165},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.5082704424858093},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.4950057864189148},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4436284303665161},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4301508665084839},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4035278260707855},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3283386826515198},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11077553033828735},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10407039523124695},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06259354948997498},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323155","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":0.7300000190734863,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4629252920","display_name":"\u57fa\u4e8e\u7a00\u758f\u6982\u7387\u56fe\u6a21\u578b\u7684\u9ad8\u5206\u8fa8\u7387\u9065\u611f\u5f71\u50cf\u573a\u666f\u8bed\u4e49\u7406\u89e3\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41771385","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":11,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2735039185","https://openalex.org/W2780861787","https://openalex.org/W2798925380","https://openalex.org/W2804199516","https://openalex.org/W2811199523","https://openalex.org/W2893801697","https://openalex.org/W2963153291","https://openalex.org/W2963270775","https://openalex.org/W2975194617","https://openalex.org/W3105636206"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W2802049774"],"abstract_inverted_index":{"Road":[0],"detection":[1,93],"from":[2],"very":[3],"high-resolution":[4],"(VHR)":[5],"remote":[6],"sensing":[7],"imagery":[8],"has":[9],"great":[10],"importance":[11],"in":[12,96],"a":[13,85],"broad":[14],"array":[15],"of":[16,35,61,143,161],"applications.":[17],"However,":[18],"the":[19,32,39,45,50,59,98,110,118,123,131,136,141,144,150,159],"most":[20],"advanced":[21],"deep":[22,88],"learning-based":[23],"methods":[24],"often":[25],"produce":[26],"fragmented":[27],"road":[28,69,82,92,137,153],"segments,":[29],"due":[30],"to":[31,104,116],"complex":[33],"backgrounds":[34],"images,":[36],"such":[37],"as":[38],"occlusions":[40],"and":[41,47,66,109,128,140],"shadows":[42],"caused":[43],"by":[44],"trees":[46],"buildings,":[48],"or":[49],"surrounding":[51],"objects":[52],"with":[53],"similar":[54],"textures.":[55],"In":[56],"this":[57],"paper,":[58],"characteristics":[60],"existing":[62],"models":[63],"were":[64,147],"analyzed":[65],"an":[67],"effective":[68],"recognition":[70,138],"method":[71],"was":[72,102,114],"explored,":[73],"we":[74],"found":[75],"that":[76],"capturing":[77],"long-range":[78],"dependencies":[79,108],"helps":[80],"improve":[81],"recognition.":[83],"Therefore,":[84],"novel":[86],"global-aware":[87],"network":[89],"(GAN)":[90],"for":[91],"is":[94],"proposed,":[95],"which":[97],"spatial-aware":[99],"module":[100,112],"(SAM)":[101],"applied":[103,115],"capture":[105,117],"spatial":[106,126],"context":[107],"channel-aware":[111],"(CAM)":[113],"interchannel":[119],"dependencies.":[120],"Through":[121],"establishing":[122],"relationships":[124],"between":[125,129],"contexts":[127],"channels,":[130],"GAN":[132],"could":[133],"effectively":[134],"alleviate":[135],"problems,":[139],"advantages":[142],"proposed":[145],"approach":[146],"validated":[148],"on":[149],"public":[151],"DeepGlobe":[152],"dataset.":[154],"The":[155],"experimental":[156],"result":[157],"demonstrates":[158],"superiority":[160],"our":[162],"method.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}