{"id":"https://openalex.org/W3080897988","doi":"https://doi.org/10.1109/tpami.2020.3018491","title":"Unambiguous Text Localization, Retrieval, and Recognition for Cluttered Scenes","display_name":"Unambiguous Text Localization, Retrieval, and Recognition for Cluttered Scenes","publication_year":2020,"publication_date":"2020-08-21","ids":{"openalex":"https://openalex.org/W3080897988","doi":"https://doi.org/10.1109/tpami.2020.3018491","mag":"3080897988","pmid":"https://pubmed.ncbi.nlm.nih.gov/32822292"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2020.3018491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.3018491","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":null,"display_name":"Xuejian Rong","orcid":"https://orcid.org/0000-0001-6617-9582"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]},{"id":"https://openalex.org/I4210093530","display_name":"City College","ror":"https://ror.org/00h90tg62","country_code":"US","type":"education","lineage":["https://openalex.org/I4210093530"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xuejian Rong","raw_affiliation_strings":["Department of Electrical Engineering, The City College, City University of New York, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The City College, City University of New York, New York, NY, USA","institution_ids":["https://openalex.org/I174216632","https://openalex.org/I4210093530","https://openalex.org/I125687163"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chucai Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I121847817","display_name":"The Graduate Center, CUNY","ror":"https://ror.org/00awd9g61","country_code":"US","type":"education","lineage":["https://openalex.org/I121847817"]},{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chucai Yi","raw_affiliation_strings":["Google on Augmented Reality, Mountain View, CA, USA","Graduate Center, City University of New York, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google on Augmented Reality, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Graduate Center, City University of New York, New York, NY, USA","institution_ids":["https://openalex.org/I174216632","https://openalex.org/I121847817"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yingli Tian","orcid":"https://orcid.org/0000-0003-4458-360X"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]},{"id":"https://openalex.org/I4210093530","display_name":"City College","ror":"https://ror.org/00h90tg62","country_code":"US","type":"education","lineage":["https://openalex.org/I4210093530"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingli Tian","raw_affiliation_strings":["Department of Electrical Engineering, The City College, City University of New York, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The City College, City University of New York, New York, NY, USA","institution_ids":["https://openalex.org/I174216632","https://openalex.org/I4210093530","https://openalex.org/I125687163"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125687163","https://openalex.org/I174216632","https://openalex.org/I4210093530"],"apc_list":null,"apc_paid":null,"fwci":0.5888,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.69432655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"44","issue":"3","first_page":"1638","last_page":"1652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8303999900817871,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8303999900817871,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.120899997651577,"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/T10028","display_name":"Topic Modeling","score":0.008799999952316284,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5375999808311462},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5275999903678894},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49810001254081726},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4593000113964081},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.4375},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42899999022483826},{"id":"https://openalex.org/keywords/text-recognition","display_name":"Text recognition","score":0.42640000581741333},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4138999879360199},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4097000062465668},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.3930000066757202}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8162999749183655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7206000089645386},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5375999808311462},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.535099983215332},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5275999903678894},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.4375},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.42640000581741333},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4097000062465668},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C151375590","wikidata":"https://www.wikidata.org/wiki/Q17147076","display_name":"Noisy text analytics","level":4,"score":0.3840000033378601},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.36500000953674316},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29499998688697815},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25459998846054077}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2020.3018491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.3018491","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:32822292","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32822292","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":[],"awards":[{"id":"https://openalex.org/G2025273420","display_name":null,"funder_award_id":"EFRI-1137172","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2419155976","display_name":null,"funder_award_id":"IIP-1343402","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3930469214","display_name":null,"funder_award_id":"IIS-1400802","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":92,"referenced_works":["https://openalex.org/W70975097","https://openalex.org/W607748843","https://openalex.org/W974261621","https://openalex.org/W1521064364","https://openalex.org/W1773149199","https://openalex.org/W1892016050","https://openalex.org/W1903029394","https://openalex.org/W1905882502","https://openalex.org/W1922126009","https://openalex.org/W1935817682","https://openalex.org/W1947481528","https://openalex.org/W1967140047","https://openalex.org/W2008806374","https://openalex.org/W2019478948","https://openalex.org/W2028277005","https://openalex.org/W2037227137","https://openalex.org/W2049705550","https://openalex.org/W2056518953","https://openalex.org/W2061802763","https://openalex.org/W2064675550","https://openalex.org/W2077069816","https://openalex.org/W2083442372","https://openalex.org/W2092399515","https://openalex.org/W2117539524","https://openalex.org/W2122221966","https://openalex.org/W2125447031","https://openalex.org/W2142159465","https://openalex.org/W2148214126","https://openalex.org/W2153182373","https://openalex.org/W2159807109","https://openalex.org/W2194187530","https://openalex.org/W2247513039","https://openalex.org/W2251512949","https://openalex.org/W2302548814","https://openalex.org/W2339589954","https://openalex.org/W2343052201","https://openalex.org/W2396529792","https://openalex.org/W2407406190","https://openalex.org/W2462848072","https://openalex.org/W2474628748","https://openalex.org/W2489434015","https://openalex.org/W2519321174","https://openalex.org/W2519818067","https://openalex.org/W2532759528","https://openalex.org/W2550687635","https://openalex.org/W2579549467","https://openalex.org/W2591644541","https://openalex.org/W2594041210","https://openalex.org/W2605127024","https://openalex.org/W2605736949","https://openalex.org/W2605982830","https://openalex.org/W2607855566","https://openalex.org/W2747107070","https://openalex.org/W2777652944","https://openalex.org/W2788069964","https://openalex.org/W2795619303","https://openalex.org/W2810983211","https://openalex.org/W2831607544","https://openalex.org/W2895741527","https://openalex.org/W2905498003","https://openalex.org/W2920582597","https://openalex.org/W2962810613","https://openalex.org/W2962811161","https://openalex.org/W2962986948","https://openalex.org/W2963037989","https://openalex.org/W2963109634","https://openalex.org/W2963115613","https://openalex.org/W2963186101","https://openalex.org/W2963327605","https://openalex.org/W2963536419","https://openalex.org/W2963650529","https://openalex.org/W2963735856","https://openalex.org/W2963758027","https://openalex.org/W2964296749","https://openalex.org/W2964685115","https://openalex.org/W2965336788","https://openalex.org/W2967615747","https://openalex.org/W2987563462","https://openalex.org/W2988326850","https://openalex.org/W3005436539","https://openalex.org/W3082397598","https://openalex.org/W6636382570","https://openalex.org/W6637373629","https://openalex.org/W6637484576","https://openalex.org/W6638742206","https://openalex.org/W6676647902","https://openalex.org/W6678846912","https://openalex.org/W6679436768","https://openalex.org/W6684191040","https://openalex.org/W6691603626","https://openalex.org/W6735439709","https://openalex.org/W6738331400"],"related_works":[],"abstract_inverted_index":{"Text":[0],"instance":[1,70,114],"as":[2],"one":[3],"category":[4],"of":[5,32,103,111,172,187,219],"self-described":[6],"objects":[7],"provides":[8],"valuable":[9],"information":[10,157],"for":[11,222],"understanding":[12,31],"and":[13,19,54,64,130,154,162,190,206,217,229],"describing":[14],"cluttered":[15,73,105],"scenes.":[16],"The":[17],"rich":[18],"precise":[20],"high-level":[21],"semantics":[22],"embodied":[23],"in":[24,71,136],"the":[25,30,33,99,185,215,223],"text":[26,58,69,90,113,120,134,145,152,165,178,194,203,211,226],"could":[27],"drastically":[28],"benefit":[29],"world":[34],"around":[35],"us.":[36],"While":[37],"most":[38],"recent":[39],"visual":[40],"phrase":[41],"grounding":[42],"approaches":[43],"focus":[44],"on":[45,200],"general":[46],"objects,":[47],"this":[48,83],"paper":[49],"explores":[50],"extracting":[51],"designated":[52],"texts":[53],"predicting":[55],"unambiguous":[56],"scene":[57,106,202,210,225],"information,":[59],"i.e.,":[60],"to":[61,96,183],"accurately":[62],"localize":[63],"recognize":[65],"a":[66,72,86,104,109,142,159,169,176,207],"specific":[67],"targeted":[68],"image":[74,107],"from":[75],"natural":[76],"language":[77],"descriptions":[78],"(referring":[79],"expressions).":[80],"To":[81],"address":[82],"issue,":[84],"first":[85],"novel":[87],"recurrent":[88,160,177],"dense":[89],"localization":[91],"network":[92],"(DTLN)":[93],"is":[94,181],"proposed":[95],"sequentially":[97],"decode":[98],"intermediate":[100],"convolutional":[101],"representations":[102],"into":[108],"set":[110],"distinct":[112],"detections.":[115],"Our":[116],"approach":[117],"avoids":[118],"repeated":[119],"detections":[121],"at":[122],"multiple":[123],"scales":[124],"by":[125,168],"recurrently":[126],"memorizing":[127],"previous":[128],"detections,":[129],"effectively":[131],"tackles":[132],"crowded":[133],"instances":[135,153],"close":[137],"proximity.":[138],"Second,":[139],"we":[140],"propose":[141],"context":[143,156,173],"reasoning":[144],"retrieval":[146,212],"(CRTR)":[147],"model,":[148],"which":[149],"jointly":[150],"encodes":[151],"their":[155],"through":[158],"network,":[161],"ranks":[163],"localized":[164],"bounding":[166],"boxes":[167],"scoring":[170],"function":[171],"compatibility.":[174],"Third,":[175],"recognition":[179,230],"module":[180],"introduced":[182],"extend":[184],"applicability":[186],"aforementioned":[188],"DTLN":[189],"CRTR":[191],"models,":[192],"via":[193],"verification":[195],"or":[196],"transcription.":[197],"Quantitative":[198],"evaluations":[199],"standard":[201],"extraction":[204],"benchmarks":[205],"newly":[208],"collected":[209],"dataset":[213],"demonstrate":[214],"effectiveness":[216],"advantages":[218],"our":[220],"models":[221],"joint":[224],"localization,":[227],"retrieval,":[228],"task.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2020-09-01T00:00:00"}