{"id":"https://openalex.org/W3032592799","doi":"https://doi.org/10.1109/tii.2020.2998107","title":"A Novel Visual Measurement Framework for Land Vehicle Positioning Based on Multimodule Cascaded Deep Neural Network","display_name":"A Novel Visual Measurement Framework for Land Vehicle Positioning Based on Multimodule Cascaded Deep Neural Network","publication_year":2020,"publication_date":"2020-05-27","ids":{"openalex":"https://openalex.org/W3032592799","doi":"https://doi.org/10.1109/tii.2020.2998107","mag":"3032592799"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2020.2998107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.2998107","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5003728041","display_name":"Zhiyong Zheng","orcid":"https://orcid.org/0000-0002-8116-129X"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyong Zheng","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100699659","display_name":"Xu Li","orcid":"https://orcid.org/0000-0003-2772-7114"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Li","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102097523","display_name":"Zhengliang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengliang Sun","raw_affiliation_strings":["Ministry of Public Security, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Public Security, Wuxi, China","institution_ids":["https://openalex.org/I1302611135"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064457872","display_name":"Xiang Song","orcid":"https://orcid.org/0000-0002-1704-4339"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Song","raw_affiliation_strings":["Nanjing Xiaozhuang University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Xiaozhuang University, Nanjing, China","institution_ids":["https://openalex.org/I4210128418"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003728041"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":1.7637,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.84888229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"17","issue":"4","first_page":"2347","last_page":"2356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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/global-positioning-system","display_name":"Global Positioning System","score":0.7420991659164429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6981052160263062},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6928613781929016},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6647936701774597},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5903818607330322},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5534666180610657},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5280424356460571},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5240336060523987},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.48321592807769775},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47515010833740234},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.41751521825790405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3232472240924835},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11011713743209839}],"concepts":[{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.7420991659164429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6981052160263062},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6928613781929016},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6647936701774597},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5903818607330322},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5534666180610657},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5280424356460571},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5240336060523987},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.48321592807769775},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47515010833740234},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.41751521825790405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3232472240924835},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11011713743209839},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2020.2998107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.2998107","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G1380177118","display_name":null,"funder_award_id":"41904024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6442879921","display_name":null,"funder_award_id":"18KJB413007","funder_id":"https://openalex.org/F4320335440","funder_display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China"},{"id":"https://openalex.org/G7294854559","display_name":null,"funder_award_id":"61973079","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/F4320335440","display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1612997784","https://openalex.org/W1698746845","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1970675587","https://openalex.org/W1980026261","https://openalex.org/W1990004830","https://openalex.org/W2076945774","https://openalex.org/W2081303520","https://openalex.org/W2095593770","https://openalex.org/W2102664783","https://openalex.org/W2146023544","https://openalex.org/W2163470068","https://openalex.org/W2277132981","https://openalex.org/W2321627895","https://openalex.org/W2343459490","https://openalex.org/W2344992754","https://openalex.org/W2419448466","https://openalex.org/W2560323025","https://openalex.org/W2707890836","https://openalex.org/W2761287863","https://openalex.org/W2762439315","https://openalex.org/W2775524044","https://openalex.org/W2806585810","https://openalex.org/W2883659536","https://openalex.org/W2885415355","https://openalex.org/W2887238201","https://openalex.org/W2887782657","https://openalex.org/W2912348842","https://openalex.org/W2946653342","https://openalex.org/W2963287528","https://openalex.org/W2963377935","https://openalex.org/W2963881378","https://openalex.org/W3101531460","https://openalex.org/W3103648783","https://openalex.org/W4293406525","https://openalex.org/W6639824700","https://openalex.org/W6717372056","https://openalex.org/W6739917289"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"This":[0],"article":[1],"proposes":[2],"a":[3,113],"novel":[4],"visual":[5],"measurement":[6],"framework,":[7],"multimodule":[8],"cascaded":[9],"deep":[10],"neural":[11,57],"network":[12,48,58],"(MMC-DNN),":[13],"to":[14,67,87,101],"achieve":[15],"accurate,":[16],"reliable,":[17],"and":[18,55,82,106],"cost-effective":[19],"vehicle":[20],"positioning":[21,94,143],"in":[22,141],"complex":[23],"urban":[24],"environments.":[25],"The":[26,62],"MMC-DNN":[27],"is":[28,64,85,99,125],"inspired":[29],"by":[30,128],"the":[31,34,70,74,83,88,97,110,118,121,135,138],"mechanism":[32],"of":[33,41,112,137],"human":[35],"eyes'":[36],"lateral":[37,104],"positioning,":[38],"which":[39],"consists":[40],"three":[42],"modules":[43],"called":[44],"siamesed":[45],"fully":[46,51],"convolutional":[47,52],"(S-FCN),":[49],"skip-connection":[50],"autoencoder":[53],"(SC-FCAE),":[54],"multitask":[56],"regressor":[59],"(MT-NNR),":[60],"respectively.":[61],"S-FCN":[63],"first":[65],"designed":[66],"accurately":[68],"detect":[69],"road":[71,76,114],"area.":[72],"Then,":[73],"segmented":[75],"was":[77],"executed":[78],"inverse":[79],"perspective":[80],"mapping":[81],"result":[84],"fed":[86],"developed":[89],"SC-FCAE":[90],"for":[91],"extracting":[92],"equivalent":[93],"features.":[95],"Furthermore,":[96],"MT-NNR":[98],"proposed":[100,139],"efficiently":[102],"estimate":[103],"position":[105],"yaw":[107],"angle":[108],"with":[109],"help":[111],"map.":[115],"Based":[116],"on":[117],"estimation":[119],"results,":[120],"MEMS":[122],"INS/GPS":[123],"integration":[124],"significantly":[126],"augmented":[127],"extended":[129],"Kalman":[130],"filter.":[131],"Experimental":[132],"results":[133],"validate":[134],"effectiveness":[136],"framework":[140],"enhancing":[142],"performance.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
