{"id":"https://openalex.org/W4389747948","doi":"https://doi.org/10.1109/tiv.2023.3342801","title":"LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving","display_name":"LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving","publication_year":2023,"publication_date":"2023-12-14","ids":{"openalex":"https://openalex.org/W4389747948","doi":"https://doi.org/10.1109/tiv.2023.3342801"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2023.3342801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3342801","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","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/A5085681305","display_name":"Yunxiao Shan","orcid":"https://orcid.org/0000-0001-8266-2312"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]},{"id":"https://openalex.org/I4391012567","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)","ror":"https://ror.org/03swgqh13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012567"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunxiao Shan","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China","Shenzhen Institute, Sun Yat-sen University, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-8266-2312","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I4210106122","https://openalex.org/I4391012567"]},{"raw_affiliation_string":"Shenzhen Institute, Sun Yat-sen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102026650","display_name":"Yao Fu","orcid":"https://orcid.org/0009-0000-0193-2254"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]},{"id":"https://openalex.org/I4391012567","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)","ror":"https://ror.org/03swgqh13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012567"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Fu","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0000-0193-2254","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I4210106122","https://openalex.org/I4391012567"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033003876","display_name":"Xiangchun Chen","orcid":"https://orcid.org/0009-0002-2257-5764"},"institutions":[{"id":"https://openalex.org/I4210115169","display_name":"Second Artillery General Hospital of Chinese People's Liberation Army","ror":"https://ror.org/0264qnp36","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210115169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangchun Chen","raw_affiliation_strings":["PLA Army Academy of Artillery and Air Defense, Hefei, Anhui, China"],"raw_orcid":"https://orcid.org/0009-0002-2257-5764","affiliations":[{"raw_affiliation_string":"PLA Army Academy of Artillery and Air Defense, Hefei, Anhui, China","institution_ids":["https://openalex.org/I4210115169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040999282","display_name":"Hongquan Lin","orcid":"https://orcid.org/0000-0002-1842-6830"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]},{"id":"https://openalex.org/I4391012567","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)","ror":"https://ror.org/03swgqh13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012567"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongquan Lin","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-1842-6830","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I4210106122","https://openalex.org/I4391012567"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067793233","display_name":"Ziquan Zhang","orcid":"https://orcid.org/0009-0004-0331-8636"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210106122","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","ror":"https://ror.org/00y7mag53","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106122"]},{"id":"https://openalex.org/I4391012567","display_name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)","ror":"https://ror.org/03swgqh13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012567"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziquan Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0004-0331-8636","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, Guangdong, China","institution_ids":["https://openalex.org/I4210106122","https://openalex.org/I4391012567"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101436312","display_name":"Jun Lin","orcid":"https://orcid.org/0000-0003-2140-551X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Lin","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China","Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-2140-551X","affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100768452","display_name":"Kai Huang","orcid":"https://orcid.org/0000-0003-0359-7810"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Huang","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-0359-7810","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5085681305"],"corresponding_institution_ids":["https://openalex.org/I157773358","https://openalex.org/I4210106122","https://openalex.org/I4391012567"],"apc_list":null,"apc_paid":null,"fwci":1.1943,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78349811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"9","issue":"2","first_page":"3544","last_page":"3557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9815000295639038,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9696000218391418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6878319382667542},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.67551589012146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6493701934814453},{"id":"https://openalex.org/keywords/unmanned-ground-vehicle","display_name":"Unmanned ground vehicle","score":0.5841108560562134},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5637983083724976},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5337076783180237},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5171391367912292},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.49699094891548157},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45857101678848267},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45799025893211365},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44922131299972534},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42667779326438904},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.4245795011520386},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.303230881690979},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13102591037750244},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.12222626805305481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6878319382667542},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.67551589012146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6493701934814453},{"id":"https://openalex.org/C2776548393","wikidata":"https://www.wikidata.org/wiki/Q2031473","display_name":"Unmanned ground vehicle","level":2,"score":0.5841108560562134},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5637983083724976},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5337076783180237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5171391367912292},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.49699094891548157},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45857101678848267},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45799025893211365},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44922131299972534},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42667779326438904},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.4245795011520386},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.303230881690979},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13102591037750244},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.12222626805305481},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/tiv.2023.3342801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3342801","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1812586646","display_name":null,"funder_award_id":"62232008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5041595446","display_name":null,"funder_award_id":"2020A1515110199","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1485699345","https://openalex.org/W1996118086","https://openalex.org/W2026520611","https://openalex.org/W2070724998","https://openalex.org/W2132360065","https://openalex.org/W2154844948","https://openalex.org/W2172108060","https://openalex.org/W2401247923","https://openalex.org/W2413995699","https://openalex.org/W2614543743","https://openalex.org/W2737444374","https://openalex.org/W2801372589","https://openalex.org/W2805521962","https://openalex.org/W2807096024","https://openalex.org/W2883141961","https://openalex.org/W2891733872","https://openalex.org/W2896315990","https://openalex.org/W2904140897","https://openalex.org/W2932012013","https://openalex.org/W2956134899","https://openalex.org/W2963881378","https://openalex.org/W2971265822","https://openalex.org/W2998152504","https://openalex.org/W3003731597","https://openalex.org/W3040741167","https://openalex.org/W3082486589","https://openalex.org/W3090824357","https://openalex.org/W3092168917","https://openalex.org/W3103520796","https://openalex.org/W3107625963","https://openalex.org/W3127367339","https://openalex.org/W3160962507","https://openalex.org/W3164142155","https://openalex.org/W3206517480","https://openalex.org/W4200457877","https://openalex.org/W4220907072","https://openalex.org/W4285209317","https://openalex.org/W4312711505","https://openalex.org/W4384916988","https://openalex.org/W4385194699","https://openalex.org/W4386918913","https://openalex.org/W6750617008","https://openalex.org/W6786506283"],"related_works":["https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W2159307582","https://openalex.org/W3150144014","https://openalex.org/W2166449590","https://openalex.org/W4385170637","https://openalex.org/W2024135719","https://openalex.org/W4281652912","https://openalex.org/W2027854881","https://openalex.org/W2153812487"],"abstract_inverted_index":{"Traversable":[0],"regions":[1,40,77,115],"identification":[2,41],"technology":[3],"plays":[4],"a":[5,37,49,79,90],"crucial":[6],"role":[7],"in":[8,16,45,110],"ensuring":[9],"safe":[10],"driving":[11],"for":[12],"unmanned":[13],"ground":[14],"vehicles":[15],"off-road":[17,35],"environments.":[18],"However,":[19],"the":[20,32,58,75,83],"unstructured":[21],"terrain":[22],"makes":[23],"it":[24],"challenging":[25],"to":[26,56,73,123,130],"identify":[27],"traversable":[28,39,59,76],"regions.":[29],"To":[30],"enhance":[31],"safety":[33],"of":[34,121,128],"driving,":[36],"LiDAR-based":[38],"method":[42,70],"is":[43,54,71],"proposed":[44,100],"this":[46],"paper.":[47],"Firstly,":[48],"deep":[50],"learning-based":[51],"neural":[52],"network":[53],"used":[55],"segment":[57],"regions,":[60],"obstacles,":[61,117],"and":[62,82,107,116,125],"vegetation.":[63],"Next,":[64],"an":[65],"improved":[66],"Gaussian":[67],"Process(GP)-based":[68],"modeling":[69],"designed":[72],"model":[74],"with":[78,89,118],"leading":[80],"speed,":[81],"obstacle":[84],"point":[85],"clouds":[86],"are":[87],"refined":[88],"composite":[91],"filter.":[92],"Finally,":[93],"field":[94],"experiments":[95],"have":[96],"demonstrated":[97],"that":[98],"our":[99],"scheme":[101],"outperforms":[102],"existing":[103],"state-of-the-art":[104],"(SOTA)":[105],"traditional":[106],"deep-learning-based":[108],"methods":[109],"accurately":[111],"identifying":[112],"both":[113],"road":[114],"precision":[119],"improvements":[120,127],"up":[122,129],"14%":[124],"recall":[126],"9%.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
