{"id":"https://openalex.org/W2743353723","doi":"https://doi.org/10.1109/tits.2017.2724138","title":"Traffic Scene Segmentation Based on RGB-D Image and Deep Learning","display_name":"Traffic Scene Segmentation Based on RGB-D Image and Deep Learning","publication_year":2017,"publication_date":"2017-08-10","ids":{"openalex":"https://openalex.org/W2743353723","doi":"https://doi.org/10.1109/tits.2017.2724138","mag":"2743353723"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2017.2724138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2724138","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/A5083033930","display_name":"Linhui Li","orcid":"https://orcid.org/0000-0002-2667-8800"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linhui Li","raw_affiliation_strings":["Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071419774","display_name":"Bo Qian","orcid":"https://orcid.org/0000-0002-6964-220X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Qian","raw_affiliation_strings":["Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101846162","display_name":"Jing Lian","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Lian","raw_affiliation_strings":["Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-6684-5722","affiliations":[{"raw_affiliation_string":"Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103871659","display_name":"Weina Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weina Zheng","raw_affiliation_strings":["Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047249127","display_name":"Yafu Zhou","orcid":"https://orcid.org/0000-0001-6985-2189"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yafu Zhou","raw_affiliation_strings":["Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Vehicle Engineering and Mechanics, School of Automotive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1406,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.95255087,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"19","issue":"5","first_page":"1664","last_page":"1669"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9983999729156494,"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/T11019","display_name":"Image Enhancement Techniques","score":0.998199999332428,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8434591293334961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7615807056427002},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6929111480712891},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6920599937438965},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6805654168128967},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6756948232650757},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6396868228912354},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5872109532356262},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5824337601661682},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.47152742743492126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3809244632720947}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8434591293334961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615807056427002},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6929111480712891},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6920599937438965},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6805654168128967},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6756948232650757},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6396868228912354},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5872109532356262},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5824337601661682},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.47152742743492126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3809244632720947}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2017.2724138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2724138","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":[{"score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2813865461","display_name":null,"funder_award_id":"61203171","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4364885363","display_name":null,"funder_award_id":"61473057","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W360623563","https://openalex.org/W1507506748","https://openalex.org/W1565402342","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1910657905","https://openalex.org/W1938976761","https://openalex.org/W2015207482","https://openalex.org/W2092623244","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2110764733","https://openalex.org/W2112796928","https://openalex.org/W2132891752","https://openalex.org/W2141200610","https://openalex.org/W2150066425","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2171943915","https://openalex.org/W2340897893","https://openalex.org/W2351389512","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2963881378","https://openalex.org/W6605121731","https://openalex.org/W6630336748","https://openalex.org/W6638667902","https://openalex.org/W6639204139","https://openalex.org/W6684191040","https://openalex.org/W6705174527"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W1999008862","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2551987074"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,17,42,55,145,159],"of":[2,37,43,56,104,135],"traffic":[3,44,57],"scenes":[4,58],"has":[5,31],"potential":[6],"applications":[7],"in":[8],"intelligent":[9],"transportation":[10],"systems.":[11],"Deep":[12],"learning":[13],"techniques":[14],"can":[15,139],"improve":[16,142],"accuracy,":[18],"especially":[19],"when":[20],"the":[21,35,41,72,102,105,116,119,133,136,143],"information":[22],"from":[23],"depth":[24,38],"maps":[25,39],"is":[26],"introduced.":[27],"However,":[28],"little":[29],"research":[30],"been":[32],"done":[33],"on":[34,60],"application":[36],"to":[40,80,141],"scene.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"propose":[50],"a":[51,82,88],"method":[52,77,120],"for":[53,96],"semantic":[54,97,144],"based":[59],"RGB-D":[61,110],"images":[62,111,125],"and":[63,71,114,147,157],"deep":[64,90],"learning.":[65],"The":[66,128],"semi-global":[67],"stereo":[68],"matching":[69],"algorithm":[70],"fast":[73],"global":[74],"image":[75],"smoothing":[76],"are":[78],"employed":[79],"obtain":[81],"smooth":[83],"disparity":[84,137],"map.":[85],"We":[86,100],"present":[87],"new":[89],"fully":[91],"convolutional":[92],"neural":[93],"network":[94,107,151],"architecture":[95,108,152],"pixel-wise":[98],"segmentation.":[99],"test":[101],"performance":[103,156],"proposed":[106,150],"using":[109],"as":[112,126],"input":[113],"compare":[115],"results":[117,130],"with":[118],"that":[121,132,148],"only":[122],"takes":[123],"RGB":[124],"input.":[127],"experimental":[129],"show":[131],"introduction":[134],"map":[138],"help":[140],"accuracy":[146],"our":[149],"achieves":[153],"good":[154],"real-time":[155],"competitive":[158],"accuracy.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
