{"id":"https://openalex.org/W2594652239","doi":"https://doi.org/10.1109/tits.2017.2665658","title":"Road Recognition From Remote Sensing Imagery Using Incremental Learning","display_name":"Road Recognition From Remote Sensing Imagery Using Incremental Learning","publication_year":2017,"publication_date":"2017-03-11","ids":{"openalex":"https://openalex.org/W2594652239","doi":"https://doi.org/10.1109/tits.2017.2665658","mag":"2594652239"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2017.2665658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2665658","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5032383728","display_name":"Jing Zhang","orcid":"https://orcid.org/0000-0003-1290-0738"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Zhang","raw_affiliation_strings":["Signal and Information Processing Laboratory, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Signal and Information Processing Laboratory, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605099","display_name":"Chen L\u00fc","orcid":"https://orcid.org/0000-0003-1927-2391"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Chen","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115076700","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0003-4887-923X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448036","display_name":"Zhuo Li","orcid":"https://orcid.org/0000-0002-9937-2669"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhuo","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111504451","display_name":"Qi Tian","orcid":"https://orcid.org/0009-0003-2676-5300"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Department of Computer Science, University of Texas at San Antonio, San Antonio, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Texas at San Antonio, San Antonio, TX, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000337879","display_name":"Liang Xi","orcid":"https://orcid.org/0000-0002-2736-829X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Liang","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5032383728"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":4.2356,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93243598,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"18","issue":"11","first_page":"2993","last_page":"3005"},"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":0.9966999888420105,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6072410941123962},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.5390410423278809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5383521318435669},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.531389594078064},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4668930768966675},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46584758162498474},{"id":"https://openalex.org/keywords/road-traffic","display_name":"Road traffic","score":0.41062334179878235},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3602309823036194},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.35676679015159607},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.22811970114707947},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22619551420211792},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.22448816895484924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6072410941123962},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.5390410423278809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383521318435669},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.531389594078064},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4668930768966675},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46584758162498474},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.41062334179878235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3602309823036194},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35676679015159607},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.22811970114707947},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22619551420211792},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.22448816895484924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2017.2665658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2665658","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.75}],"awards":[{"id":"https://openalex.org/G1173409498","display_name":null,"funder_award_id":"61370189","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G243942729","display_name":null,"funder_award_id":"4142009","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G3639115482","display_name":null,"funder_award_id":"61372149","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4009065917","display_name":null,"funder_award_id":"4163071","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G7927928483","display_name":null,"funder_award_id":"61471013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8961798258","display_name":null,"funder_award_id":"61531006","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/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1480020587","https://openalex.org/W1554821638","https://openalex.org/W1584279007","https://openalex.org/W1927406451","https://openalex.org/W1964038289","https://openalex.org/W1972916106","https://openalex.org/W1973600165","https://openalex.org/W1979363725","https://openalex.org/W1979516310","https://openalex.org/W1984204905","https://openalex.org/W2006976206","https://openalex.org/W2032718344","https://openalex.org/W2043002547","https://openalex.org/W2045354372","https://openalex.org/W2057105140","https://openalex.org/W2075383976","https://openalex.org/W2078816540","https://openalex.org/W2092332012","https://openalex.org/W2095210813","https://openalex.org/W2103559027","https://openalex.org/W2104847084","https://openalex.org/W2105700564","https://openalex.org/W2106300334","https://openalex.org/W2112583669","https://openalex.org/W2120820227","https://openalex.org/W2128272608","https://openalex.org/W2130931342","https://openalex.org/W2134316834","https://openalex.org/W2143972956","https://openalex.org/W2145892879","https://openalex.org/W2147323433","https://openalex.org/W2155912251","https://openalex.org/W2161969291","https://openalex.org/W2167502421","https://openalex.org/W2214725774","https://openalex.org/W2322335119","https://openalex.org/W3105104152","https://openalex.org/W4235041442","https://openalex.org/W6646388057","https://openalex.org/W6674035541"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W4375867731","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167"],"abstract_inverted_index":{"Roads,":[0],"as":[1,148,173,175],"important":[2],"artificial":[3],"objects,":[4],"are":[5,134,146],"the":[6,20,27,38,51,96,100,114,120,131,144,154,180],"main":[7],"body":[8],"of":[9,22,53,157],"modern":[10],"traffic":[11],"system,":[12],"providing":[13],"many":[14],"conveniences":[15],"for":[16,84],"human":[17],"civilization.":[18],"With":[19],"development":[21],"Intelligent":[23],"Transportation":[24],"Systems":[25],"(ITS),":[26],"road":[28,39,46,59,64,81,115,121,132,137,150,170],"structure":[29],"is":[30,35,105,117],"changing":[31],"frequently.":[32],"Road":[33],"recognition":[34,82,171,177],"to":[36,57,153],"identify":[37],"type":[40],"from":[41,119,136],"remote":[42,85,102,122],"sensing":[43,86,103,123],"imagery,":[44],"and":[45,61,71,139,142],"types":[47,151],"depend":[48],"largely":[49],"on":[50],"characteristics":[52],"roads.":[54],"Thus,":[55],"how":[56],"extract":[58],"features":[60,133],"further":[62],"making":[63],"classification":[65,155],"efficient":[66],"have":[67],"become":[68],"a":[69,80],"popular":[70,182],"challenging":[72],"research":[73],"topic.":[74],"In":[75,91],"this":[76],"paper,":[77],"we":[78],"propose":[79],"method":[83,94,167],"imagery":[87,104,124],"using":[88,109],"incremental":[89,158],"learning.":[90],"principle,":[92],"our":[93,166],"includes":[95],"following":[97],"steps:":[98],"1)":[99],"non-road":[101],"first":[106],"filtered":[107],"by":[108,125],"support":[110],"vector":[111],"machine;":[112],"2)":[113],"network":[116,138],"obtained":[118],"computing":[126],"multiple":[127],"saliency":[128],"features;":[129],"3)":[130],"extracted":[135],"background":[140],"environment;":[141],"4)":[143],"roads":[145],"recognized":[147],"three":[149],"according":[152],"results":[156,163],"learning":[159],"algorithm.":[160],"The":[161],"experimental":[162],"show":[164],"that":[165],"has":[168],"higher":[169],"rate":[172],"well":[174],"less":[176],"time":[178],"than":[179],"other":[181],"algorithms.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}