{"id":"https://openalex.org/W2904736494","doi":"https://doi.org/10.1109/geoinformatics.2018.8557145","title":"Applying CNN Classifier to Road Interchange Classification","display_name":"Applying CNN Classifier to Road Interchange Classification","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2904736494","doi":"https://doi.org/10.1109/geoinformatics.2018.8557145","mag":"2904736494"},"language":"en","primary_location":{"id":"doi:10.1109/geoinformatics.2018.8557145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2018.8557145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th International Conference on Geoinformatics","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/A5068437966","display_name":"HE Haiwei","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"H.E. Haiwei","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024762618","display_name":"Haizhong Qian","orcid":"https://orcid.org/0000-0002-8125-7750"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Haizhong","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017502310","display_name":"Xie Limin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie Limin","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056026082","display_name":"Duan Peixiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan Peixiang","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068437966"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3767,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66980367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9901000261306763,"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/T11106","display_name":"Data Management and Algorithms","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7797838449478149},{"id":"https://openalex.org/keywords/raster-graphics","display_name":"Raster graphics","score":0.6446470618247986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6400924921035767},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6256158947944641},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5876131057739258},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5523112416267395},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47114816308021545},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4583513140678406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4474230408668518},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4155157208442688},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35259509086608887},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16752541065216064}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7797838449478149},{"id":"https://openalex.org/C181844469","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster graphics","level":2,"score":0.6446470618247986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6400924921035767},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6256158947944641},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5876131057739258},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5523112416267395},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47114816308021545},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4583513140678406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4474230408668518},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4155157208442688},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35259509086608887},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16752541065216064},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/geoinformatics.2018.8557145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2018.8557145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th International Conference on Geoinformatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1504581647","https://openalex.org/W1512139451","https://openalex.org/W1549735104","https://openalex.org/W2019174570","https://openalex.org/W2100495367","https://openalex.org/W2147800946","https://openalex.org/W2150341604","https://openalex.org/W2155541015","https://openalex.org/W2347115704","https://openalex.org/W2361084681","https://openalex.org/W2393311998","https://openalex.org/W2746032333","https://openalex.org/W2753857816","https://openalex.org/W2950094539","https://openalex.org/W2998383847","https://openalex.org/W4205947740","https://openalex.org/W4294375521","https://openalex.org/W6682778277","https://openalex.org/W6707032007","https://openalex.org/W6743028545","https://openalex.org/W6744120721","https://openalex.org/W6772345004"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661","https://openalex.org/W2005234362","https://openalex.org/W1997235926"],"abstract_inverted_index":{"The":[0,30,72],"identification":[1,35,66],"and":[2,24,44,80,92,108,119,133],"classification":[3,115],"of":[4,20,33,41,67,89,116,129,136],"interchange":[5,34,49,69,96],"structures":[6],"in":[7,98,113],"OSM":[8],"(Open":[9],"Street":[10],"Map)":[11],"data":[12,76],"can":[13],"provide":[14],"important":[15],"information":[16],"for":[17,65,123],"the":[18,38,47,68,86,90,94,114,127,130,134],"construction":[19],"multi-scale":[21],"model,":[22],"navigation":[23],"location":[25],"services,":[26],"congestion":[27],"analysis,":[28],"etc.":[29],"traditional":[31],"method":[32,59,73,104],"relies":[36],"on":[37,61],"low-level":[39],"characteristics":[40,88],"artificial":[42],"design,":[43],"cannot":[45],"distinguish":[46],"complex":[48,95,117],"structure":[50,97],"with":[51,77,126],"interferences":[52],"effectively.":[53],"In":[54],"this":[55,103],"paper,":[56],"a":[57],"new":[58],"based":[60],"convolutional":[62],"neural":[63,82,137],"network":[64,83,138],"is":[70,121],"proposed.":[71],"combines":[74],"vector":[75],"raster":[78],"image,":[79],"uses":[81],"to":[84],"learn":[85],"fuzzy":[87],"interchange,":[91],"classifies":[93],"OSM.":[99],"Experiments":[100],"show":[101],"that":[102],"has":[105,109],"strong":[106],"anti-interference,":[107],"achieved":[110],"good":[111],"results":[112],"interchanges,":[118],"there":[120],"room":[122],"further":[124],"improvement":[125],"expansion":[128],"sample":[131],"base":[132],"optimization":[135],"model.":[139]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}