{"id":"https://openalex.org/W2287002002","doi":"https://doi.org/10.3390/s16030280","title":"An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints","display_name":"An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints","publication_year":2016,"publication_date":"2016-02-24","ids":{"openalex":"https://openalex.org/W2287002002","doi":"https://doi.org/10.3390/s16030280","mag":"2287002002","pmid":"https://pubmed.ncbi.nlm.nih.gov/26927108"},"language":"en","primary_location":{"id":"doi:10.3390/s16030280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s16030280","pdf_url":"https://www.mdpi.com/1424-8220/16/3/280/pdf?version=1456311975","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/16/3/280/pdf?version=1456311975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114585213","display_name":"Shiyao Wang","orcid":"https://orcid.org/0000-0001-5291-4945"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyao Wang","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102011846","display_name":"Zhidong Deng","orcid":"https://orcid.org/0000-0001-9970-1023"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhidong Deng","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052307918","display_name":"Gang Yin","orcid":"https://orcid.org/0000-0002-0839-242X"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Yin","raw_affiliation_strings":["State Key Laboratory of Coal Mine Disaster Dynamics and Control, College of Resources and Environmental Science, Chongqing University, Chongqing 400030, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Coal Mine Disaster Dynamics and Control, College of Resources and Environmental Science, Chongqing University, Chongqing 400030, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052307918"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":9.7759,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.97991453,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"280","last_page":"280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11325","display_name":"Inertial Sensor and Navigation","score":0.9987000226974487,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.7056868076324463},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6833996772766113},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.6199769377708435},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5172110795974731},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5056722164154053},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.494956910610199},{"id":"https://openalex.org/keywords/real-time-kinematic","display_name":"Real Time Kinematic","score":0.4814709722995758},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47621259093284607},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.45621269941329956},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.45454901456832886},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.42209818959236145},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36432600021362305},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3287461996078491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31373631954193115},{"id":"https://openalex.org/keywords/gnss-applications","display_name":"GNSS applications","score":0.2229577898979187},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11328718066215515},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0849684476852417}],"concepts":[{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.7056868076324463},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833996772766113},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.6199769377708435},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5172110795974731},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5056722164154053},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.494956910610199},{"id":"https://openalex.org/C93103318","wikidata":"https://www.wikidata.org/wiki/Q980965","display_name":"Real Time Kinematic","level":4,"score":0.4814709722995758},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47621259093284607},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.45621269941329956},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.45454901456832886},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.42209818959236145},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36432600021362305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3287461996078491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31373631954193115},{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.2229577898979187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11328718066215515},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0849684476852417},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s16030280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s16030280","pdf_url":"https://www.mdpi.com/1424-8220/16/3/280/pdf?version=1456311975","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:26927108","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26927108","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a2eedb4ddba74f83b88007e2f5a9adc9","is_oa":true,"landing_page_url":"https://doaj.org/article/a2eedb4ddba74f83b88007e2f5a9adc9","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 16, Iss 3, p 280 (2016)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:3792343","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4813855","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/16/3/280/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s16030280","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 16; Issue 3; Pages: 280","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s16030280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s16030280","pdf_url":"https://www.mdpi.com/1424-8220/16/3/280/pdf?version=1456311975","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8399999737739563}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4260095629","display_name":null,"funder_award_id":"60775040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4632250340","display_name":null,"funder_award_id":"2012AA041402","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5016123089","display_name":null,"funder_award_id":"90820305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8015682759","display_name":null,"funder_award_id":"91420106","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320315254","display_name":"Innovative Research Group Project of the National Natural Science Foundation of China","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2287002002.pdf","grobid_xml":"https://content.openalex.org/works/W2287002002.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1969553439","https://openalex.org/W1973122016","https://openalex.org/W1976086917","https://openalex.org/W1979920012","https://openalex.org/W1993077520","https://openalex.org/W2002444941","https://openalex.org/W2005772744","https://openalex.org/W2005995917","https://openalex.org/W2051548137","https://openalex.org/W2053087201","https://openalex.org/W2054658115","https://openalex.org/W2058815839","https://openalex.org/W2059264085","https://openalex.org/W2070681743","https://openalex.org/W2083400934","https://openalex.org/W2085287976","https://openalex.org/W2087363050","https://openalex.org/W2095641875","https://openalex.org/W2107059967","https://openalex.org/W2114160172","https://openalex.org/W2114547915","https://openalex.org/W2122917607","https://openalex.org/W2127157498","https://openalex.org/W2135093089","https://openalex.org/W2158214504","https://openalex.org/W2158931274","https://openalex.org/W2168175751","https://openalex.org/W2169823756","https://openalex.org/W2546913570","https://openalex.org/W3087672182","https://openalex.org/W4212961835","https://openalex.org/W4242688646"],"related_works":["https://openalex.org/W2091018038","https://openalex.org/W2225378543","https://openalex.org/W9839718","https://openalex.org/W3110613631","https://openalex.org/W4287122200","https://openalex.org/W2742744817","https://openalex.org/W2040913503","https://openalex.org/W3166845860","https://openalex.org/W3202472720","https://openalex.org/W2785359964"],"abstract_inverted_index":{"A":[0],"high-performance":[1],"differential":[2],"global":[3],"positioning":[4],"system":[5],"(GPS)":[6],"receiver":[7],"with":[8],"real":[9,156],"time":[10],"kinematics":[11],"provides":[12],"absolute":[13],"localization":[14,128],"for":[15],"driverless":[16,210],"cars.":[17],"However,":[18],"it":[19],"is":[20,205],"not":[21],"only":[22],"susceptible":[23],"to":[24,30,85,110,125,180],"multipath":[25],"effect":[26],"but":[27],"also":[28],"unable":[29],"effectively":[31],"fulfill":[32],"precise":[33],"error":[34],"correction":[35],"in":[36,171,208],"a":[37,59,71,147,153],"wide":[38],"range":[39],"of":[40,61,73,90,113,134,149,155,189],"driving":[41],"areas.":[42],"This":[43],"paper":[44],"proposes":[45],"an":[46],"accurate":[47,127],"GPS-inertial":[48],"measurement":[49],"unit":[50],"(IMU)/dead":[51],"reckoning":[52],"(DR)":[53],"data":[54,116,136,202],"fusion":[55,137,203],"method":[56,165,191,204],"based":[57],"on":[58,101,152,195],"set":[60,72],"predictive":[62,103],"models":[63,89],"and":[64,75,97,105,173,199],"occupancy":[65],"grid":[66,95,142],"constraints.":[67],"First,":[68],"we":[69,145],"employ":[70],"autoregressive":[74],"moving":[76],"average":[77],"(ARMA)":[78],"equations":[79],"that":[80,117,163],"have":[81,111],"different":[82],"structural":[83],"parameters":[84],"build":[86],"maximum":[87],"likelihood":[88],"raw":[91],"navigation.":[92],"Second,":[93],"both":[94],"constraints":[96],"spatial":[98],"consensus":[99],"checks":[100],"all":[102],"results":[104,161],"current":[106],"measurements":[107],"are":[108,122],"required":[109],"removal":[112],"outliers.":[114],"Navigation":[115],"satisfy":[118],"stationary":[119],"stochastic":[120],"process":[121],"further":[123],"fused":[124],"achieve":[126],"results.":[129],"Third,":[130],"the":[131,164,186,196,200],"standard":[132],"deviation":[133],"multimodal":[135],"can":[138,166],"be":[139],"pre-specified":[140],"by":[141],"size.":[143],"Finally,":[144],"perform":[146],"lot":[148],"field":[150],"tests":[151],"diversity":[154],"urban":[157],"scenarios.":[158],"The":[159],"experimental":[160],"demonstrate":[162],"significantly":[167],"smooth":[168],"small":[169],"jumps":[170],"bias":[172],"considerably":[174],"reduce":[175],"accumulated":[176],"position":[177,187],"errors":[178],"due":[179],"DR.":[181],"With":[182],"low":[183],"computational":[184],"complexity,":[185],"accuracy":[188],"our":[190,209],"surpasses":[192],"existing":[193],"state-of-the-arts":[194],"same":[197],"dataset":[198],"new":[201],"practically":[206],"applied":[207],"car.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}