{"id":"https://openalex.org/W4290714341","doi":"https://doi.org/10.1109/tpami.2022.3196959","title":"Glance and Focus Networks for Dynamic Visual Recognition","display_name":"Glance and Focus Networks for Dynamic Visual Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4290714341","doi":"https://doi.org/10.1109/tpami.2022.3196959","pmid":"https://pubmed.ncbi.nlm.nih.gov/35939472"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3196959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3196959","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013240918","display_name":"Gao Huang","orcid":"https://orcid.org/0000-0002-7251-0988"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gao Huang","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China","Beijing Academy of Artificial Intelligence (BAAI), China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Beijing Academy of Artificial Intelligence (BAAI), China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418037","display_name":"Yulin Wang","orcid":"https://orcid.org/0000-0002-1363-0234"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulin Wang","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063536734","display_name":"Kangchen Lv","orcid":"https://orcid.org/0000-0001-5748-7372"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangchen Lv","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034603953","display_name":"Haojun Jiang","orcid":"https://orcid.org/0009-0002-0126-5564"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojun Jiang","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103005778","display_name":"Wenhui Huang","orcid":"https://orcid.org/0000-0001-8123-2441"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Huang","raw_affiliation_strings":["China Mobile Research Insitute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Insitute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074548270","display_name":"Pengfei Qi","orcid":"https://orcid.org/0000-0003-2885-2072"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Qi","raw_affiliation_strings":["China Mobile Research Insitute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Insitute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101868179","display_name":"Shiji Song","orcid":"https://orcid.org/0000-0003-0858-1770"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiji Song","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5013240918"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.8747,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.94839727,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"45","issue":"4","first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994999766349792,"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/computer-science","display_name":"Computer science","score":0.7947593331336975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7285738587379456},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5955286026000977},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5585477948188782},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5464614033699036},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5412198901176453},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5170431733131409},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48809826374053955},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4758864641189575},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4631708264350891},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.46009817719459534},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.459800660610199},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38170021772384644},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36553919315338135},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20466259121894836},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11620721220970154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947593331336975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7285738587379456},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5955286026000977},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5585477948188782},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5464614033699036},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5412198901176453},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5170431733131409},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48809826374053955},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4758864641189575},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4631708264350891},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.46009817719459534},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.459800660610199},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38170021772384644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36553919315338135},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20466259121894836},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11620721220970154},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3196959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3196959","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35939472","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35939472","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":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":105,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1566134554","https://openalex.org/W1895577753","https://openalex.org/W1905882502","https://openalex.org/W1956340063","https://openalex.org/W2047094503","https://openalex.org/W2108598243","https://openalex.org/W2119717200","https://openalex.org/W2123229215","https://openalex.org/W2157331557","https://openalex.org/W2194775991","https://openalex.org/W2271840356","https://openalex.org/W2295107390","https://openalex.org/W2300242332","https://openalex.org/W2342840547","https://openalex.org/W2549139847","https://openalex.org/W2562731582","https://openalex.org/W2625366777","https://openalex.org/W2736601468","https://openalex.org/W2737725206","https://openalex.org/W2752782242","https://openalex.org/W2770804203","https://openalex.org/W2773003563","https://openalex.org/W2799062770","https://openalex.org/W2799176631","https://openalex.org/W2883780447","https://openalex.org/W2884751099","https://openalex.org/W2889469641","https://openalex.org/W2891951760","https://openalex.org/W2945472816","https://openalex.org/W2948303601","https://openalex.org/W2955854238","https://openalex.org/W2962716320","https://openalex.org/W2962851801","https://openalex.org/W2962858109","https://openalex.org/W2962944050","https://openalex.org/W2963122961","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963393494","https://openalex.org/W2963407932","https://openalex.org/W2963918968","https://openalex.org/W2963954913","https://openalex.org/W2963993763","https://openalex.org/W2964098158","https://openalex.org/W2964259004","https://openalex.org/W2967333288","https://openalex.org/W2967733054","https://openalex.org/W2981812042","https://openalex.org/W2981963725","https://openalex.org/W2982083293","https://openalex.org/W2988396473","https://openalex.org/W2990152177","https://openalex.org/W2990495699","https://openalex.org/W2990631821","https://openalex.org/W3009073662","https://openalex.org/W3012362498","https://openalex.org/W3034429256","https://openalex.org/W3035424951","https://openalex.org/W3040398697","https://openalex.org/W3109632933","https://openalex.org/W3113299742","https://openalex.org/W3175773336","https://openalex.org/W3204647170","https://openalex.org/W3211681816","https://openalex.org/W4214661601","https://openalex.org/W4226146163","https://openalex.org/W4246193833","https://openalex.org/W4297775537","https://openalex.org/W4312960790","https://openalex.org/W6618372016","https://openalex.org/W6628927728","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638523607","https://openalex.org/W6677103964","https://openalex.org/W6680834391","https://openalex.org/W6682137061","https://openalex.org/W6685060484","https://openalex.org/W6692846177","https://openalex.org/W6693397755","https://openalex.org/W6694517276","https://openalex.org/W6704559304","https://openalex.org/W6726275242","https://openalex.org/W6732520560","https://openalex.org/W6737664043","https://openalex.org/W6741002519","https://openalex.org/W6741753902","https://openalex.org/W6743912273","https://openalex.org/W6745447533","https://openalex.org/W6751913510","https://openalex.org/W6751979845","https://openalex.org/W6753001334","https://openalex.org/W6755258449","https://openalex.org/W6755843862","https://openalex.org/W6756718674","https://openalex.org/W6756887525","https://openalex.org/W6762148536","https://openalex.org/W6762718338","https://openalex.org/W6766978945","https://openalex.org/W6767312631","https://openalex.org/W6767354860","https://openalex.org/W6784233108","https://openalex.org/W6789558952","https://openalex.org/W6802996638"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W2761785940","https://openalex.org/W2129933262","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Spatial":[0],"redundancy":[1,53],"widely":[2],"exists":[3],"in":[4,11,51,54,159],"visual":[5,80],"recognition":[6,68,218],"tasks,":[7],"i.e.,":[8],"discriminative":[9],"features":[10],"an":[12,45,245],"image":[13,67,99,214],"or":[14],"video":[15,217],"frame":[16],"usually":[17],"correspond":[18],"to":[19,31,109,116],"only":[20],"a":[21,71,92,101,110,165,211],"subset":[22],"of":[23,48,56,96,112,155,213,229,239],"pixels,":[24],"while":[25],"the":[26,32,42,66,78,83,97,136,153,205,226,236,240],"remaining":[27],"regions":[28,115,158],"are":[29,258],"irrelevant":[30],"task":[33],"at":[34,100,127,260],"hand.":[35],"Therefore,":[36],"static":[37],"models":[38,192,224,257],"which":[39,199],"process":[40,122],"all":[41],"pixels":[43],"with":[44,188,221],"equal":[46],"amount":[47],"computation":[49],"result":[50],"considerable":[52],"terms":[55],"time":[57],"and":[58,86,105,182,197,216,220,255],"space":[59],"consumption.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"formulate":[65],"problem":[69,154],"as":[70,130,164,184,194,204],"sequential":[72,121],"coarse-to-fine":[73],"feature":[74,206],"learning":[75,167],"process,":[76],"mimicking":[77],"human":[79],"system.":[81],"Specifically,":[82],"proposed":[84],"Glance":[85],"Focus":[87],"Network":[88],"(GFNet)":[89],"first":[90],"extracts":[91],"quick":[93],"global":[94],"representation":[95],"input":[98],"low":[102],"resolution":[103],"scale,":[104],"then":[106],"strategically":[107],"attends":[108],"series":[111],"salient":[113],"(small)":[114],"learn":[117],"finer":[118],"features.":[119],"The":[120],"naturally":[123],"facilitates":[124],"adaptive":[125],"inference":[126],"test":[128],"time,":[129],"it":[131,185,234],"can":[132,200],"be":[133,201],"terminated":[134],"once":[135],"model":[137,161],"is":[138,149,162,180,186],"sufficiently":[139],"confident":[140],"about":[141],"its":[142],"prediction,":[143],"avoiding":[144],"further":[145],"redundant":[146],"computation.":[147],"It":[148],"worth":[150],"noting":[151],"that":[152],"locating":[156],"discriminant":[157],"our":[160,230],"formulated":[163],"reinforcement":[166],"task,":[168],"thus":[169],"requiring":[170],"no":[171],"additional":[172],"manual":[173],"annotations":[174],"other":[175],"than":[176],"classification":[177,215],"labels.":[178],"GFNet":[179],"general":[181],"flexible":[183],"compatible":[187],"any":[189],"off-the-shelf":[190],"backbone":[191,223],"(such":[193],"MobileNets,":[195],"EfficientNets":[196],"TSM),":[198],"conveniently":[202],"deployed":[203],"extractor.":[207],"Extensive":[208],"experiments":[209],"on":[210,244],"variety":[212],"tasks":[219],"various":[222],"demonstrate":[225],"remarkable":[227],"efficiency":[228],"method.":[231],"For":[232],"example,":[233],"reduces":[235],"average":[237],"latency":[238],"highly":[241],"efficient":[242],"MobileNet-V3":[243],"iPhone":[246],"XS":[247],"Max":[248],"by":[249],"1.3x":[250],"without":[251],"sacrificing":[252],"accuracy.":[253],"Code":[254],"pre-trained":[256],"available":[259],"https://github.com/blackfeather-wang/GFNet-Pytorch.":[261]},"counts_by_year":[{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
