{"id":"https://openalex.org/W3143918648","doi":"https://doi.org/10.3390/s21072536","title":"Pedestrian Detection Using Multispectral Images and a Deep Neural Network","display_name":"Pedestrian Detection Using Multispectral Images and a Deep Neural Network","publication_year":2021,"publication_date":"2021-04-04","ids":{"openalex":"https://openalex.org/W3143918648","doi":"https://doi.org/10.3390/s21072536","mag":"3143918648","pmid":"https://pubmed.ncbi.nlm.nih.gov/33916637"},"language":"en","primary_location":{"id":"doi:10.3390/s21072536","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21072536","pdf_url":"https://www.mdpi.com/1424-8220/21/7/2536/pdf?version=1617940361","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/1424-8220/21/7/2536/pdf?version=1617940361","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001680868","display_name":"Jason Nataprawira","orcid":null},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jason Nataprawira","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070068490","display_name":"Yanlei Gu","orcid":"https://orcid.org/0000-0001-9708-7429"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yanlei Gu","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091359587","display_name":"Igor Goncharenko","orcid":"https://orcid.org/0000-0002-8063-8068"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Igor Goncharenko","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109244048","display_name":"Shunsuke Kamijo","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunsuke Kamijo","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5070068490"],"corresponding_institution_ids":["https://openalex.org/I135768898"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.1051,"has_fulltext":true,"cited_by_count":46,"citation_normalized_percentile":{"value":0.93064353,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"21","issue":"7","first_page":"2536","last_page":"2536"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9988999962806702,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.9438015818595886},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.8715857863426208},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7991979122161865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7056164741516113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7029828429222107},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5978667736053467},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5018689632415771},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49165064096450806},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.43358537554740906},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42312559485435486},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3322541117668152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3005671203136444},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22640106081962585},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19781118631362915},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.08933347463607788}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.9438015818595886},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.8715857863426208},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7991979122161865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7056164741516113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7029828429222107},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5978667736053467},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5018689632415771},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49165064096450806},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.43358537554740906},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42312559485435486},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3322541117668152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3005671203136444},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22640106081962585},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19781118631362915},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.08933347463607788}],"mesh":[{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004738","descriptor_name":"Engineering","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004738","descriptor_name":"Engineering","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004738","descriptor_name":"Engineering","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21072536","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21072536","pdf_url":"https://www.mdpi.com/1424-8220/21/7/2536/pdf?version=1617940361","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:33916637","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33916637","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:70172065dd2d4a2289ab719fce94131d","is_oa":true,"landing_page_url":"https://doaj.org/article/70172065dd2d4a2289ab719fce94131d","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 7, p 2536 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/7/2536/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21072536","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 7; Pages: 2536","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8038561","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8038561","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/s21072536","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21072536","pdf_url":"https://www.mdpi.com/1424-8220/21/7/2536/pdf?version=1617940361","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.550000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3143918648.pdf","grobid_xml":"https://content.openalex.org/works/W3143918648.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1488500354","https://openalex.org/W1536680647","https://openalex.org/W1910108985","https://openalex.org/W1982577389","https://openalex.org/W1992825118","https://openalex.org/W2074602185","https://openalex.org/W2102605133","https://openalex.org/W2107775979","https://openalex.org/W2127635871","https://openalex.org/W2127878586","https://openalex.org/W2153837630","https://openalex.org/W2161969291","https://openalex.org/W2170577464","https://openalex.org/W2193145675","https://openalex.org/W2570343428","https://openalex.org/W2575265421","https://openalex.org/W2603773317","https://openalex.org/W2608096492","https://openalex.org/W2741620214","https://openalex.org/W2781581716","https://openalex.org/W2791697444","https://openalex.org/W2796347433","https://openalex.org/W2889480448","https://openalex.org/W2896726780","https://openalex.org/W2940453295","https://openalex.org/W2953458970","https://openalex.org/W2963037989","https://openalex.org/W2991485606","https://openalex.org/W3003745590","https://openalex.org/W3007529723","https://openalex.org/W3009628433","https://openalex.org/W3023514908","https://openalex.org/W3049750233","https://openalex.org/W3083767870","https://openalex.org/W3106250896","https://openalex.org/W3112018172","https://openalex.org/W3128670286","https://openalex.org/W3133882761","https://openalex.org/W3151111735","https://openalex.org/W3160584074","https://openalex.org/W3177203279","https://openalex.org/W3206617022","https://openalex.org/W4230498685","https://openalex.org/W4247596867","https://openalex.org/W4285719527","https://openalex.org/W6683411478","https://openalex.org/W6777135113"],"related_works":["https://openalex.org/W3132270449","https://openalex.org/W4377289091","https://openalex.org/W2972620127","https://openalex.org/W3013647784","https://openalex.org/W2981141433","https://openalex.org/W2997281059","https://openalex.org/W2792279927","https://openalex.org/W4403391793","https://openalex.org/W4385497869","https://openalex.org/W283587633"],"abstract_inverted_index":{"Pedestrian":[0],"fatalities":[1],"and":[2,29,80,98,128],"injuries":[3],"most":[4],"likely":[5],"occur":[6],"in":[7,24,42,70,132,164],"vehicle-pedestrian":[8],"crashes.":[9],"Meanwhile,":[10],"engineers":[11],"have":[12],"tried":[13],"to":[14,76,84,124,169,184],"reduce":[15,185],"the":[16,33,46,86,90,104,107,112,115,118,133,145,170,174],"problems":[17],"by":[18,189],"developing":[19],"a":[20,161],"pedestrian":[21,43,52,67,108,134,149,165],"detection":[22,44,53,68,87,135,150,166,193],"function":[23],"Advanced":[25],"Driver-Assistance":[26],"Systems":[27],"(ADAS)":[28],"autonomous":[30],"vehicles.":[31],"However,":[32],"system":[34],"is":[35,45,144,182],"still":[36],"not":[37],"perfect.":[38],"A":[39],"remaining":[40],"problem":[41],"performance":[47,69,105],"reduction":[48],"at":[49,151],"nighttime,":[50],"although":[51],"should":[54],"work":[55],"well":[56],"regardless":[57],"of":[58,66,106,114,117],"lighting":[59,72,153],"conditions.":[60,154],"This":[61],"study":[62],"presents":[63],"an":[64],"evaluation":[65],"different":[71,92,152],"conditions,":[73],"then":[74],"proposes":[75],"adopt":[77],"multispectral":[78,99,142],"image":[79,93],"deep":[81,119,157],"neural":[82,120,158],"network":[83,121,159],"improve":[85],"accuracy.":[88,194],"In":[89,110],"evaluation,":[91],"sources":[94],"including":[95],"RGB,":[96],"thermal,":[97],"format":[100],"are":[101,122],"compared":[102,168],"for":[103,148,176],"detection.":[109],"addition,":[111],"optimizations":[113],"architecture":[116],"performed":[123],"achieve":[125],"high":[126],"accuracy":[127,167],"short":[129],"processing":[130,177,187],"time":[131,178,188],"task.":[136],"The":[137,155],"result":[138],"implies":[139],"that":[140,180],"using":[141],"images":[143],"best":[146],"solution":[147],"proposed":[156],"accomplishes":[160],"6.9%":[162],"improvement":[163],"baseline":[171],"method.":[172],"Moreover,":[173],"optimization":[175],"indicates":[179],"it":[181],"possible":[183],"22.76%":[186],"only":[190],"sacrificing":[191],"2%":[192]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}