{"id":"https://openalex.org/W3119139528","doi":"https://doi.org/10.3390/s21010300","title":"SynPo-Net\u2014Accurate and Fast CNN-Based 6DoF Object Pose Estimation Using Synthetic Training","display_name":"SynPo-Net\u2014Accurate and Fast CNN-Based 6DoF Object Pose Estimation Using Synthetic Training","publication_year":2021,"publication_date":"2021-01-05","ids":{"openalex":"https://openalex.org/W3119139528","doi":"https://doi.org/10.3390/s21010300","mag":"3119139528","pmid":"https://pubmed.ncbi.nlm.nih.gov/33466293"},"language":"en","primary_location":{"id":"doi:10.3390/s21010300","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010300","pdf_url":"https://www.mdpi.com/1424-8220/21/1/300/pdf?version=1609834185","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/1424-8220/21/1/300/pdf?version=1609834185","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047143300","display_name":"Yongzhi Su","orcid":"https://orcid.org/0000-0003-0843-5917"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Yongzhi Su","raw_affiliation_strings":["TU Kaiserslautern, 67663 Kaiserslautern, Germany"],"raw_orcid":"https://orcid.org/0000-0003-0843-5917","affiliations":[{"raw_affiliation_string":"TU Kaiserslautern, 67663 Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000984202","display_name":"Jason Rambach","orcid":"https://orcid.org/0000-0001-8122-6789"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jason Rambach","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046969927","display_name":"Alain Pagani","orcid":"https://orcid.org/0000-0002-5136-0837"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alain Pagani","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051650277","display_name":"Didier Stricker","orcid":"https://orcid.org/0009-0004-8794-6858"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Didier Stricker","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany","TU Kaiserslautern, 67663 Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]},{"raw_affiliation_string":"TU Kaiserslautern, 67663 Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000984202","https://openalex.org/A5047143300"],"corresponding_institution_ids":["https://openalex.org/I153267046","https://openalex.org/I33256026"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.446,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.81400432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"21","issue":"1","first_page":"300","last_page":"300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976999759674072,"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":0.9976999759674072,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.9969000220298767,"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":0.8202224969863892},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7941805124282837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7823505401611328},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.61402428150177},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5677669048309326},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.558588981628418},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5575411319732666},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5432265400886536},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5269466042518616},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4975340664386749},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4893921911716461},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4781273901462555},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41262954473495483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.372574120759964},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08065789937973022}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8202224969863892},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7941805124282837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7823505401611328},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.61402428150177},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5677669048309326},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.558588981628418},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5575411319732666},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5432265400886536},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5269466042518616},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4975340664386749},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4893921911716461},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4781273901462555},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41262954473495483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.372574120759964},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08065789937973022},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/s21010300","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010300","pdf_url":"https://www.mdpi.com/1424-8220/21/1/300/pdf?version=1609834185","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:33466293","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33466293","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:ff833ed07e05459fa4fb853417f94de2","is_oa":true,"landing_page_url":"https://doaj.org/article/ff833ed07e05459fa4fb853417f94de2","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 21, Iss 1, p 300 (2021)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:6705715","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC7796199","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/1/300/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21010300","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 21; Issue 1; Pages: 300","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7796199","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7796199","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/s21010300","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010300","pdf_url":"https://www.mdpi.com/1424-8220/21/1/300/pdf?version=1609834185","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":[{"score":0.4399999976158142,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3119139528.pdf","grobid_xml":"https://content.openalex.org/works/W3119139528.grobid-xml"},"referenced_works_count":79,"referenced_works":["https://openalex.org/W62794737","https://openalex.org/W764651262","https://openalex.org/W1022526533","https://openalex.org/W1526868886","https://openalex.org/W1591870335","https://openalex.org/W1686810756","https://openalex.org/W1909903157","https://openalex.org/W1965818182","https://openalex.org/W2031489346","https://openalex.org/W2071634722","https://openalex.org/W2097117768","https://openalex.org/W2101199297","https://openalex.org/W2117228865","https://openalex.org/W2122585444","https://openalex.org/W2158890580","https://openalex.org/W2161168419","https://openalex.org/W2194775991","https://openalex.org/W2200124539","https://openalex.org/W2315410813","https://openalex.org/W2317063912","https://openalex.org/W2472269674","https://openalex.org/W2474655341","https://openalex.org/W2488101876","https://openalex.org/W2574567538","https://openalex.org/W2584009249","https://openalex.org/W2604236302","https://openalex.org/W2604662268","https://openalex.org/W2605111497","https://openalex.org/W2613718673","https://openalex.org/W2738401084","https://openalex.org/W2756202949","https://openalex.org/W2756627269","https://openalex.org/W2765653652","https://openalex.org/W2767032778","https://openalex.org/W2768840867","https://openalex.org/W2768879211","https://openalex.org/W2771008497","https://openalex.org/W2787908438","https://openalex.org/W2796347433","https://openalex.org/W2797527871","https://openalex.org/W2888752296","https://openalex.org/W2894651257","https://openalex.org/W2895410314","https://openalex.org/W2895439318","https://openalex.org/W2909314588","https://openalex.org/W2910399693","https://openalex.org/W2942881172","https://openalex.org/W2949117887","https://openalex.org/W2949481100","https://openalex.org/W2950025457","https://openalex.org/W2951336016","https://openalex.org/W2951553744","https://openalex.org/W2951747365","https://openalex.org/W2952019568","https://openalex.org/W2953021746","https://openalex.org/W2953106684","https://openalex.org/W2953240077","https://openalex.org/W2962869576","https://openalex.org/W2962956488","https://openalex.org/W2963177347","https://openalex.org/W2963188159","https://openalex.org/W2963203908","https://openalex.org/W2963288137","https://openalex.org/W2963709863","https://openalex.org/W2963756608","https://openalex.org/W2963881378","https://openalex.org/W2963892972","https://openalex.org/W2964056579","https://openalex.org/W2964249569","https://openalex.org/W2981854237","https://openalex.org/W2984163771","https://openalex.org/W2986197551","https://openalex.org/W2998787775","https://openalex.org/W3009516594","https://openalex.org/W3024485546","https://openalex.org/W3034986117","https://openalex.org/W3100052745","https://openalex.org/W3103919331","https://openalex.org/W6720266987"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2113785214","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4281696776","https://openalex.org/W3089306886","https://openalex.org/W4294967731"],"abstract_inverted_index":{"Estimation":[0],"and":[1,20,61,65,107,115,148],"tracking":[2,169],"of":[3,6,14,38,46,58,86,145],"6DoF":[4,90,158],"poses":[5],"objects":[7,47,87],"in":[8,143],"images":[9,45,85,117],"is":[10,98,123],"a":[11,71,75,99,108,161,168],"challenging":[12],"problem":[13],"great":[15],"importance":[16],"for":[17,29,104,126],"robotic":[18],"interaction":[19],"augmented":[21],"reality.":[22],"Recent":[23],"approaches":[24],"applying":[25],"deep":[26],"neural":[27],"networks":[28],"pose":[30,54,105,159],"estimation":[31],"have":[32],"shown":[33],"encouraging":[34],"results.":[35],"However,":[36],"most":[37],"them":[39],"rely":[40],"on":[41,82],"training":[42,62,142],"with":[43,48],"real":[44,114],"severe":[49],"limitations":[50],"concerning":[51],"ground":[52],"truth":[53],"acquisition,":[55],"full":[56],"coverage":[57],"possible":[59],"poses,":[60],"dataset":[63],"scaling":[64],"generalization":[66],"capability.":[67],"This":[68],"paper":[69],"presents":[70],"novel":[72],"approach":[73,135],"using":[74,140],"Convolutional":[76],"Neural":[77],"Network":[78],"(CNN)":[79],"trained":[80],"exclusively":[81],"single-channel":[83],"Synthetic":[84],"to":[88,155,171],"regress":[89],"object":[91],"Poses":[92],"directly":[93],"(SynPo-Net).":[94],"The":[95,129],"proposed":[96,109],"SynPo-Net":[97],"network":[100],"architecture":[101],"specifically":[102],"designed":[103],"regression":[106],"domain":[110,121],"adaptation":[111],"scheme":[112],"transforming":[113],"synthetic":[116,141],"into":[118,167],"an":[119],"intermediate":[120],"that":[122,133],"better":[124],"fit":[125],"establishing":[127],"correspondences.":[128],"extensive":[130],"evaluation":[131],"shows":[132],"our":[134],"significantly":[136],"outperforms":[137],"the":[138,157,173],"state-of-the-art":[139],"terms":[144],"both":[146],"accuracy":[147],"speed.":[149],"Our":[150],"system":[151,170],"can":[152],"be":[153,165],"used":[154],"estimate":[156],"from":[160],"single":[162],"frame,":[163],"or":[164],"integrated":[166],"provide":[172],"initial":[174],"pose.":[175]},"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":4},{"year":2021,"cited_by_count":5}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
