{"id":"https://openalex.org/W4366091475","doi":"https://doi.org/10.3390/rs15082088","title":"Detector\u2013Tracker Integration Framework for Autonomous Vehicles Pedestrian Tracking","display_name":"Detector\u2013Tracker Integration Framework for Autonomous Vehicles Pedestrian Tracking","publication_year":2023,"publication_date":"2023-04-15","ids":{"openalex":"https://openalex.org/W4366091475","doi":"https://doi.org/10.3390/rs15082088"},"language":"en","primary_location":{"id":"doi:10.3390/rs15082088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082088","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2088/pdf?version=1681555638","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/8/2088/pdf?version=1681555638","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017341063","display_name":"Huanhuan Wang","orcid":"https://orcid.org/0000-0002-6957-8017"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanhuan Wang","raw_affiliation_strings":["School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043654176","display_name":"Lisheng Jin","orcid":"https://orcid.org/0000-0002-3086-1333"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lisheng Jin","raw_affiliation_strings":["Hebei Key Laboratory of Special Delivery Equipment, Yanshan University, Qinhuangdao 066004, China","School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"Hebei Key Laboratory of Special Delivery Equipment, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]},{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021662942","display_name":"Yang He","orcid":"https://orcid.org/0000-0002-2257-6073"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang He","raw_affiliation_strings":["School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019612199","display_name":"Zhen Huo","orcid":"https://orcid.org/0000-0002-2226-5224"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Huo","raw_affiliation_strings":["School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000338415","display_name":"Guangqi Wang","orcid":"https://orcid.org/0009-0008-3557-1141"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangqi Wang","raw_affiliation_strings":["School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031077836","display_name":"Xinyu Sun","orcid":"https://orcid.org/0000-0002-6518-6411"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Sun","raw_affiliation_strings":["School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066004, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043654176"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.3896,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90560399,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"15","issue":"8","first_page":"2088","last_page":"2088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.812946081161499},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6506257653236389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6414127349853516},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.627977728843689},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5962205529212952},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5874966382980347},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5862249135971069},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5248171091079712},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5172865390777588},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.4591069221496582},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.42033863067626953},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.31338199973106384},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.13440078496932983},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07687437534332275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.812946081161499},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6506257653236389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6414127349853516},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.627977728843689},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5962205529212952},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5874966382980347},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5862249135971069},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5248171091079712},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5172865390777588},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.4591069221496582},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.42033863067626953},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.31338199973106384},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.13440078496932983},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07687437534332275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15082088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082088","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2088/pdf?version=1681555638","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5ddaf08e66244a419a309dcb20a6d253","is_oa":true,"landing_page_url":"https://doaj.org/article/5ddaf08e66244a419a309dcb20a6d253","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 8, p 2088 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/8/2088/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15082088","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":"Remote Sensing; Volume 15; Issue 8; Pages: 2088","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15082088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082088","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2088/pdf?version=1681555638","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G2623194539","display_name":null,"funder_award_id":"CXZZBS2023061","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2677904528","display_name":null,"funder_award_id":"2021YFB3202200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5270818542","display_name":null,"funder_award_id":"52072333","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5575890943","display_name":null,"funder_award_id":"2021YFB3202200","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6904583345","display_name":null,"funder_award_id":"CXZZBS2023061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G732650669","display_name":null,"funder_award_id":"52072333","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4366091475.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2252355370","https://openalex.org/W2531409750","https://openalex.org/W2565639579","https://openalex.org/W2594507094","https://openalex.org/W2603203130","https://openalex.org/W2739491435","https://openalex.org/W2749203358","https://openalex.org/W2787237028","https://openalex.org/W2889935068","https://openalex.org/W2897582990","https://openalex.org/W2910234817","https://openalex.org/W2911075534","https://openalex.org/W2962927175","https://openalex.org/W2963037989","https://openalex.org/W2964137095","https://openalex.org/W2966535964","https://openalex.org/W2967533163","https://openalex.org/W2984145721","https://openalex.org/W2989604896","https://openalex.org/W3034240185","https://openalex.org/W3034679090","https://openalex.org/W3035410385","https://openalex.org/W3037210613","https://openalex.org/W3084173793","https://openalex.org/W3095753995","https://openalex.org/W3096609285","https://openalex.org/W3099887740","https://openalex.org/W3104218139","https://openalex.org/W3106250896","https://openalex.org/W3113093028","https://openalex.org/W3116469262","https://openalex.org/W3119686997","https://openalex.org/W3156279252","https://openalex.org/W3159824803","https://openalex.org/W3162405170","https://openalex.org/W3163648926","https://openalex.org/W3164698655","https://openalex.org/W3167976421","https://openalex.org/W3183519347","https://openalex.org/W3194543418","https://openalex.org/W3207282964","https://openalex.org/W4221162155","https://openalex.org/W4225130202","https://openalex.org/W4286904999","https://openalex.org/W4310467366","https://openalex.org/W4312473433","https://openalex.org/W4319298639","https://openalex.org/W4319866011","https://openalex.org/W4327652243","https://openalex.org/W4360863476"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2318603563","https://openalex.org/W887692824","https://openalex.org/W2354419434","https://openalex.org/W4285271403","https://openalex.org/W3178626677","https://openalex.org/W2110357291","https://openalex.org/W3015801620","https://openalex.org/W377974473"],"abstract_inverted_index":{"Pedestrian":[0],"tracking":[1,22,136,152,163,215],"is":[2,24,97,114,199],"an":[3],"important":[4],"aspect":[5],"of":[6,18,35,50,88,138,204,216],"autonomous":[7,61,217],"vehicles":[8],"environment":[9],"perception":[10],"in":[11,172,181,196,201],"a":[12,56,66,91,108,202],"vehicle":[13,62],"running":[14],"environment.":[15],"The":[16],"performance":[17,137],"the":[19,27,31,38,45,72,85,101,115,135,139,148,159,173,182,193,213],"existing":[20],"pedestrian":[21,63,67,214],"algorithms":[23],"limited":[25],"by":[26,144,170,179],"complex":[28],"traffic":[29],"environment,":[30],"changeable":[32],"appearance":[33,93],"characteristics":[34],"pedestrians":[36],"and":[37,48,126,130,134,176,207],"frequent":[39],"occlusion":[40],"interaction,":[41],"which":[42,99,113],"leads":[43],"to":[44,83,106,212],"insufficient":[46],"accuracy":[47],"stability":[49],"tracking.":[51,64],"Therefore,":[52],"this":[53,197],"paper":[54,198],"proposes":[55],"detector\u2013tracker":[57],"integration":[58],"framework":[59,141,160,194],"for":[60],"Firstly,":[65],"objects":[68],"detector":[69],"based":[70],"on":[71,124,188],"improved":[73],"YOLOv7":[74],"network":[75,87,96],"was":[76,81,142],"established.":[77],"Space-to-Depth":[78],"convolution":[79],"layer":[80],"adopted":[82],"improve":[84],"backbone":[86],"YOLOv7.":[89],"Then,":[90],"novel":[92],"feature":[94,110],"extraction":[95,111],"proposed,":[98],"integrates":[100],"convolutional":[102],"structural":[103],"re-parameterization":[104],"idea":[105],"construct":[107],"full-scale":[109],"block,":[112],"optimized":[116],"DeepSORT":[117],"tracker.":[118],"Finally,":[119],"experiments":[120],"were":[121],"carried":[122],"out":[123],"MOT17":[125,174],"MOT20":[127,183],"public":[128],"datasets":[129],"driving":[131,190],"video":[132,191],"sequences,":[133,192],"proposed":[140,195],"evaluated":[143],"comparing":[145],"it":[146],"with":[147,166],"most":[149],"advanced":[150],"multi-object":[151],"algorithms.":[153],"Quantitative":[154],"analysis":[155],"results":[156],"show":[157],"that":[158],"has":[161],"high":[162],"accuracy.":[164],"Compared":[165],"DeepSORT,":[167],"MOTA":[168,177],"improves":[169,178],"2.3%":[171],"dataset":[175],"4.2%":[180],"dataset.":[184],"Through":[185],"qualitative":[186],"evaluation":[187],"real":[189],"robust":[200],"variety":[203],"climate":[205],"environments,":[206],"can":[208],"be":[209],"effectively":[210],"applied":[211],"vehicles.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
