{"id":"https://openalex.org/W2941395802","doi":"https://doi.org/10.1109/vcip.2018.8698718","title":"Roads Detection of Aerial Image with FCN-CRF Model","display_name":"Roads Detection of Aerial Image with FCN-CRF Model","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2941395802","doi":"https://doi.org/10.1109/vcip.2018.8698718","mag":"2941395802"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2018.8698718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2018.8698718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Visual Communications and Image Processing (VCIP)","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/A5049713946","display_name":"Yunbo Rao","orcid":"https://orcid.org/0000-0001-5433-7379"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunbo Rao","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100737761","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-7223-1137"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102942783","display_name":"Jiansu Pu","orcid":"https://orcid.org/0000-0002-4284-6958"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiansu Pu","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029055781","display_name":"Jianhua Deng","orcid":"https://orcid.org/0000-0003-0427-5717"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Deng","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101733972","display_name":"Qifei Wang","orcid":"https://orcid.org/0009-0000-5276-5118"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qifei Wang","raw_affiliation_strings":["EECS, University of California, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"EECS, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049713946"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.9705,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.77127827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9998999834060669,"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":0.9998999834060669,"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/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":0.9976000189781189,"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/normalization","display_name":"Normalization (sociology)","score":0.8030602931976318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7575287222862244},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7464737296104431},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7005928158760071},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.5789194703102112},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5689449310302734},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5606901049613953},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5451157093048096},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5190768837928772},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48973894119262695},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4710685610771179},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4317779242992401},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.4196073114871979},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41712820529937744},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22740432620048523},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12875327467918396}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8030602931976318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7575287222862244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7464737296104431},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7005928158760071},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.5789194703102112},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5689449310302734},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5606901049613953},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5451157093048096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5190768837928772},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48973894119262695},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4710685610771179},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4317779242992401},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.4196073114871979},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41712820529937744},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22740432620048523},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12875327467918396},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip.2018.8698718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2018.8698718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6399999856948853,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1996777517","https://openalex.org/W2124592697","https://openalex.org/W2416190443","https://openalex.org/W2469938794","https://openalex.org/W2592583011","https://openalex.org/W2623331213","https://openalex.org/W2949117887","https://openalex.org/W2962685937","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6678459986","https://openalex.org/W6697462184","https://openalex.org/W6720435667","https://openalex.org/W6734561925","https://openalex.org/W7020680850"],"related_works":["https://openalex.org/W2369061952","https://openalex.org/W2367122702","https://openalex.org/W1601492201","https://openalex.org/W2132989621","https://openalex.org/W2015447694","https://openalex.org/W2383495548","https://openalex.org/W2370645350","https://openalex.org/W1969590113","https://openalex.org/W4283696875","https://openalex.org/W3110585990"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,36],"deep":[4],"learning":[5],"based":[6],"model":[7,90,97,112],"for":[8,23,71],"roads":[9],"detection":[10,26],"in":[11,27,88,103],"Aerial":[12],"image.":[13,30],"In":[14],"general,":[15],"standard":[16],"CNN":[17],"networks":[18],"would":[19],"have":[20],"less":[21],"ability":[22],"tiny":[24],"objects":[25],"remote":[28],"sensing":[29],"With":[31],"this":[32],"regard,":[33],"we":[34],"propose":[35],"novel":[37],"fully":[38],"convolutional":[39],"network,":[40],"which":[41],"utilizes":[42],"deconvolution":[43],"layers":[44],"and":[45,54,81,117],"feature":[46],"map":[47],"fussing":[48],"to":[49,66,91,115],"take":[50],"as":[51,63],"input":[52,65],"intensity":[53],"pixel-wise":[55],"labeling.":[56],"Moreover,":[57],"the":[58,64,72,93,108],"class":[59],"prediction":[60],"are":[61],"used":[62,87],"Condition":[67],"Random":[68],"Field":[69],"(CRF)":[70],"final":[73],"pixel":[74],"prediction.":[75],"The":[76],"Batch":[77],"Normalization":[78],"(BN)":[79],"algorithm":[80],"two":[82],"stages":[83],"training":[84],"strategy":[85],"were":[86],"our":[89,111],"reduce":[92],"time":[94,118],"cost":[95],"of":[96,110],"training.":[98],"Several":[99],"experimental":[100],"results":[101],"conducted":[102],"Massachuseets.":[104],"Road":[105],"dataset":[106],"demonstrate":[107],"superiority":[109],"with":[113],"respect":[114],"accuracy":[116],"cost.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
