{"id":"https://openalex.org/W2981683113","doi":"https://doi.org/10.3390/rs11212499","title":"Road Extraction of High-Resolution Remote Sensing Images Derived from DenseUNet","display_name":"Road Extraction of High-Resolution Remote Sensing Images Derived from DenseUNet","publication_year":2019,"publication_date":"2019-10-25","ids":{"openalex":"https://openalex.org/W2981683113","doi":"https://doi.org/10.3390/rs11212499","mag":"2981683113"},"language":"en","primary_location":{"id":"doi:10.3390/rs11212499","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11212499","pdf_url":"https://www.mdpi.com/2072-4292/11/21/2499/pdf?version=1572001094","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/21/2499/pdf?version=1572001094","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101541733","display_name":"Xin Jiang","orcid":"https://orcid.org/0000-0003-4141-1538"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Xin","raw_affiliation_strings":["Department of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China"],"affiliations":[{"raw_affiliation_string":"Department of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037230519","display_name":"Xinchang Zhang","orcid":"https://orcid.org/0000-0001-8463-9757"},"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":"Xinchang Zhang","raw_affiliation_strings":["School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China"],"affiliations":[{"raw_affiliation_string":"School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101530019","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0002-3507-6078"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhang","raw_affiliation_strings":["College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China"],"affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101397729","display_name":"Fang Wu","orcid":"https://orcid.org/0000-0001-8431-3079"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Fang","raw_affiliation_strings":["College of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China"],"affiliations":[{"raw_affiliation_string":"College of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037230519"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":12.3103,"has_fulltext":true,"cited_by_count":114,"citation_normalized_percentile":{"value":0.99203388,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":"21","first_page":"2499","last_page":"2499"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9894999861717224,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9890000224113464,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7734514474868774},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6170216798782349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5343771576881409},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5282940864562988},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.48342812061309814},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4743432104587555},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.45831412076950073},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4390527009963989},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36818164587020874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33128368854522705},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3006535768508911},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11302325129508972}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7734514474868774},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6170216798782349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5343771576881409},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5282940864562988},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.48342812061309814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4743432104587555},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.45831412076950073},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4390527009963989},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36818164587020874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33128368854522705},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3006535768508911},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11302325129508972},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs11212499","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11212499","pdf_url":"https://www.mdpi.com/2072-4292/11/21/2499/pdf?version=1572001094","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:53be5e6107014c5aa0f12ab099b45758","is_oa":true,"landing_page_url":"https://doaj.org/article/53be5e6107014c5aa0f12ab099b45758","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 21, p 2499 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/21/2499/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11212499","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 11; Issue 21; Pages: 2499","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11212499","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11212499","pdf_url":"https://www.mdpi.com/2072-4292/11/21/2499/pdf?version=1572001094","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","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/G1628471651","display_name":null,"funder_award_id":"Grant No. GZIT2016-A5-147","funder_id":"https://openalex.org/F4320327063","funder_display_name":"National Administration of Surveying, Mapping and Geoinformation of China"},{"id":"https://openalex.org/G193332973","display_name":null,"funder_award_id":"41875122, 41431178, 41801351, 41671453","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2044893531","display_name":null,"funder_award_id":"2016A030311016","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/G2788401638","display_name":null,"funder_award_id":"4167145","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2981101543","display_name":null,"funder_award_id":"41801351","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2983406743","display_name":null,"funder_award_id":"2018001","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"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/G4277810417","display_name":null,"funder_award_id":"41431178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4916234390","display_name":null,"funder_award_id":"41875122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5311346577","display_name":null,"funder_award_id":"2018001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5441714955","display_name":null,"funder_award_id":"GZIT2016-A5-147","funder_id":"https://openalex.org/F4320327063","funder_display_name":"National Administration of Surveying, Mapping and Geoinformation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","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/G6634672948","display_name":null,"funder_award_id":"41671453","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8208342437","display_name":null,"funder_award_id":"1 and","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},{"id":"https://openalex.org/F4320327063","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2981683113.pdf","grobid_xml":"https://content.openalex.org/works/W2981683113.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W73112891","https://openalex.org/W1528110553","https://openalex.org/W1745334888","https://openalex.org/W1832693441","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1974097572","https://openalex.org/W1984288883","https://openalex.org/W2015785930","https://openalex.org/W2022508996","https://openalex.org/W2042302914","https://openalex.org/W2050560048","https://openalex.org/W2050888744","https://openalex.org/W2061413575","https://openalex.org/W2081729065","https://openalex.org/W2098180043","https://openalex.org/W2109530046","https://openalex.org/W2113221323","https://openalex.org/W2148143831","https://openalex.org/W2154579312","https://openalex.org/W2155806169","https://openalex.org/W2156044350","https://openalex.org/W2156163116","https://openalex.org/W2163200524","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2228908729","https://openalex.org/W2250966211","https://openalex.org/W2416190443","https://openalex.org/W2546821789","https://openalex.org/W2560023338","https://openalex.org/W2593886839","https://openalex.org/W2594203750","https://openalex.org/W2595964094","https://openalex.org/W2623331213","https://openalex.org/W2774320778","https://openalex.org/W2787091153","https://openalex.org/W2798925380","https://openalex.org/W2886645875","https://openalex.org/W2886934227","https://openalex.org/W2890554434","https://openalex.org/W2893801697","https://openalex.org/W2905810301","https://openalex.org/W2907583485","https://openalex.org/W2908020915","https://openalex.org/W2919115771","https://openalex.org/W2921476973","https://openalex.org/W2934268922","https://openalex.org/W2938004456","https://openalex.org/W2942366787","https://openalex.org/W2943295486","https://openalex.org/W2945957599","https://openalex.org/W2949395449","https://openalex.org/W2952632681","https://openalex.org/W2952637581","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2981849677","https://openalex.org/W2994962692","https://openalex.org/W4255437949","https://openalex.org/W6631792978","https://openalex.org/W6682602794","https://openalex.org/W6716302598","https://openalex.org/W7020680850"],"related_works":["https://openalex.org/W1989735375","https://openalex.org/W2034727732","https://openalex.org/W2127305659","https://openalex.org/W2050609384","https://openalex.org/W1992574978","https://openalex.org/W2054964223","https://openalex.org/W4379231730","https://openalex.org/W2901309398","https://openalex.org/W2076169979","https://openalex.org/W2050634715"],"abstract_inverted_index":{"Road":[0,21],"network":[1,79,114],"extraction":[2,22,150],"is":[3,122],"one":[4],"of":[5,36,52,96,107,118,127],"the":[6,37,64,67,77,105,119,143],"significant":[7],"assignments":[8],"for":[9,148],"disaster":[10],"emergency":[11],"response,":[12],"intelligent":[13],"transportation":[14],"systems,":[15],"and":[16,49,58,91,100],"real-time":[17],"updating":[18],"road":[19,78,149],"network.":[20],"base":[23],"on":[24,41,124],"high-resolution":[25,128],"remote":[26,81],"sensing":[27,82],"images":[28,83,129],"has":[29],"become":[30],"a":[31,72,85],"hot":[32],"topic.":[33],"Presently,":[34],"most":[35],"researches":[38],"are":[39,47,61],"based":[40],"traditional":[42],"machine":[43],"learning":[44],"algorithms,":[45],"which":[46,103],"complex":[48,152],"computational":[50],"because":[51],"impervious":[53],"surfaces":[54],"such":[55],"as":[56],"roads":[57],"buildings":[59],"that":[60,142],"discernible":[62],"in":[63,151],"images.":[65],"Given":[66],"above":[68],"problems,":[69],"we":[70],"propose":[71],"new":[73],"method":[74,121,144],"to":[75],"extract":[76],"from":[80],"using":[84],"DenseUNet":[86,94],"model":[87],"with":[88,132],"few":[89],"parameters":[90],"robust":[92],"characteristics.":[93],"consists":[95],"dense":[97],"connection":[98],"units":[99],"skips":[101],"connections,":[102],"strengthens":[104],"fusion":[106],"different":[108],"scales":[109],"by":[110,130],"connections":[111],"at":[112],"various":[113],"layers.":[115],"The":[116,138],"performance":[117],"advanced":[120],"validated":[123],"two":[125],"datasets":[126],"comparison":[131],"three":[133],"classical":[134],"semantic":[135],"segmentation":[136],"methods.":[137],"experimental":[139],"results":[140],"show":[141],"can":[145],"be":[146],"used":[147],"scenes.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":8}],"updated_date":"2026-04-19T08:26:33.389920","created_date":"2025-10-10T00:00:00"}