{"id":"https://openalex.org/W2974841803","doi":"https://doi.org/10.3390/s19184028","title":"A Lane Detection Method Based on a Ridge Detector and Regional G-RANSAC","display_name":"A Lane Detection Method Based on a Ridge Detector and Regional G-RANSAC","publication_year":2019,"publication_date":"2019-09-18","ids":{"openalex":"https://openalex.org/W2974841803","doi":"https://doi.org/10.3390/s19184028","mag":"2974841803","pmid":"https://pubmed.ncbi.nlm.nih.gov/31540518"},"language":"en","primary_location":{"id":"doi:10.3390/s19184028","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19184028","pdf_url":"https://www.mdpi.com/1424-8220/19/18/4028/pdf?version=1568978781","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/1424-8220/19/18/4028/pdf?version=1568978781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035244277","display_name":"Zefeng Lu","orcid":"https://orcid.org/0000-0001-7220-4529"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zefeng Lu","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075489504","display_name":"Ying Xu","orcid":"https://orcid.org/0000-0002-2881-7093"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Xu","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":"https://orcid.org/0000-0002-2881-7093","affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037969067","display_name":"Xin Shan","orcid":"https://orcid.org/0000-0003-3775-0131"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Shan","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Licai Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licai Liu","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051526485","display_name":"Xingzheng Wang","orcid":"https://orcid.org/0000-0002-5433-3631"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingzheng Wang","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102723742","display_name":"Jianhao Shen","orcid":"https://orcid.org/0000-0002-4977-7959"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhao Shen","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5075489504"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.8637,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.76656792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"19","issue":"18","first_page":"4028","last_page":"4028"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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":0.9998000264167786,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9829999804496765,"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/ransac","display_name":"RANSAC","score":0.9534751176834106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6223564147949219},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5938165187835693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.589137077331543},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5298753976821899},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.4953066408634186},{"id":"https://openalex.org/keywords/division","display_name":"Division (mathematics)","score":0.4603680372238159},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44284120202064514},{"id":"https://openalex.org/keywords/corner-detection","display_name":"Corner detection","score":0.4346919059753418},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43223002552986145},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42972102761268616},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41845598816871643},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3552880585193634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2629814147949219},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24592536687850952},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11002933979034424}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.9534751176834106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6223564147949219},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5938165187835693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.589137077331543},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5298753976821899},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.4953066408634186},{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.4603680372238159},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44284120202064514},{"id":"https://openalex.org/C39499422","wikidata":"https://www.wikidata.org/wiki/Q697320","display_name":"Corner detection","level":3,"score":0.4346919059753418},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43223002552986145},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42972102761268616},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41845598816871643},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3552880585193634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2629814147949219},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24592536687850952},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11002933979034424},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s19184028","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19184028","pdf_url":"https://www.mdpi.com/1424-8220/19/18/4028/pdf?version=1568978781","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:31540518","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31540518","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:ae892aa2dd0441dfbcb1a6cf3b06292b","is_oa":true,"landing_page_url":"https://doaj.org/article/ae892aa2dd0441dfbcb1a6cf3b06292b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 19, Iss 18, p 4028 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/18/4028/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19184028","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","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6767126","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6767126","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s19184028","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19184028","pdf_url":"https://www.mdpi.com/1424-8220/19/18/4028/pdf?version=1568978781","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":[],"awards":[{"id":"https://openalex.org/G4035820044","display_name":null,"funder_award_id":"51577120","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G573117559","display_name":null,"funder_award_id":"61403259","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":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2974841803.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W949980965","https://openalex.org/W1977431488","https://openalex.org/W1980026261","https://openalex.org/W1995995493","https://openalex.org/W2002179820","https://openalex.org/W2030168736","https://openalex.org/W2039544046","https://openalex.org/W2040046539","https://openalex.org/W2042105889","https://openalex.org/W2051077519","https://openalex.org/W2082747607","https://openalex.org/W2087816846","https://openalex.org/W2118545852","https://openalex.org/W2118573797","https://openalex.org/W2135293965","https://openalex.org/W2136929315","https://openalex.org/W2137097255","https://openalex.org/W2159132531","https://openalex.org/W2161977181","https://openalex.org/W2277132981","https://openalex.org/W2480315820","https://openalex.org/W2514143496","https://openalex.org/W2554079827","https://openalex.org/W2734118241","https://openalex.org/W2766067901","https://openalex.org/W2790715811","https://openalex.org/W2794363460","https://openalex.org/W2801378207","https://openalex.org/W2806943411","https://openalex.org/W2889687301","https://openalex.org/W2890572967","https://openalex.org/W2895338961","https://openalex.org/W2902889243","https://openalex.org/W2903311463","https://openalex.org/W2914663064","https://openalex.org/W2942265110","https://openalex.org/W2943086675","https://openalex.org/W2944033393","https://openalex.org/W2944630113","https://openalex.org/W2945919933","https://openalex.org/W2959033806","https://openalex.org/W2964199920","https://openalex.org/W2969113418","https://openalex.org/W2971030196","https://openalex.org/W3081229243","https://openalex.org/W3125996993","https://openalex.org/W4237272725","https://openalex.org/W6641547041"],"related_works":["https://openalex.org/W2082346459","https://openalex.org/W2384529544","https://openalex.org/W2534909612","https://openalex.org/W2362110088","https://openalex.org/W2119399348","https://openalex.org/W1565457536","https://openalex.org/W2900021640","https://openalex.org/W2185842017","https://openalex.org/W2006302445","https://openalex.org/W2024019664"],"abstract_inverted_index":{"Lane":[0],"detection":[1,16,104],"plays":[2],"an":[3,69,81],"important":[4],"role":[5],"in":[6,24,139,160],"improving":[7],"autopilot's":[8],"safety.":[9],"In":[10],"this":[11,101],"paper,":[12],"a":[13,53,108],"novel":[14,102],"lane-division-lines":[15,76],"method":[17,136],"is":[18,39,56],"proposed,":[19],"which":[20],"exhibits":[21],"good":[22],"performances":[23,99,132],"abnormal":[25],"illumination":[26],"and":[27,64,124,148,153,157],"lane":[28,103,113,123],"occlusion.":[29],"It":[30],"includes":[31],"three":[32],"major":[33],"components:":[34],"First,":[35],"the":[36,75,88,98,112,118,130,134],"captured":[37],"image":[38],"converted":[40],"to":[41,44,58],"aerial":[42],"view":[43],"make":[45],"full":[46],"use":[47],"of":[48,100,133,164],"parallel":[49],"lanes'":[50],"characteristics.":[51],"Second,":[52],"ridge":[54],"detector":[55],"proposed":[57,107,135],"extract":[59],"each":[60],"lane's":[61],"feature":[62],"points":[63,67],"remove":[65],"noise":[66],"with":[68],"adaptable":[70],"neural":[71],"network":[72],"(ANN).":[73],"Last,":[74],"are":[77],"accurately":[78],"fitted":[79],"by":[80],"improved":[82],"random":[83,92],"sample":[84,93],"consensus":[85,94],"(RANSAC),":[86],"termed":[87],"(regional)":[89],"gaussian":[90],"distribution":[91],"(G-RANSAC).":[95],"To":[96],"test":[97],"method,":[105],"we":[106],"new":[109],"index":[110,115],"named":[111],"departure":[114,119],"(LDI)":[116],"describing":[117],"degree":[120],"between":[121],"true":[122],"predicted":[125],"lane.":[126],"Experimental":[127],"results":[128],"verified":[129],"superior":[131],"over":[137],"others":[138],"different":[140,162],"testing":[141,165],"scenarios,":[142],"respectively":[143],"achieving":[144],"99.02%,":[145],"96.92%,":[146],"96.65%":[147],"91.61%":[149],"true-positive":[150],"rates":[151],"(TPR);":[152],"66.16,":[154],"54.85,":[155],"55.98":[156],"52.61":[158],"LDIs":[159],"four":[161],"types":[163],"scenarios.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
