{"id":"https://openalex.org/W4387757582","doi":"https://doi.org/10.1109/tpami.2023.3325533","title":"Explanatory Object Part Aggregation for Zero-Shot Learning","display_name":"Explanatory Object Part Aggregation for Zero-Shot Learning","publication_year":2023,"publication_date":"2023-10-18","ids":{"openalex":"https://openalex.org/W4387757582","doi":"https://doi.org/10.1109/tpami.2023.3325533","pmid":"https://pubmed.ncbi.nlm.nih.gov/37851556"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3325533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3325533","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/A5100633270","display_name":"Xin Chen","orcid":"https://orcid.org/0000-0003-2903-5525"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Chen","raw_affiliation_strings":["College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2903-5525","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053583417","display_name":"Xiaoling Deng","orcid":"https://orcid.org/0000-0001-5588-3443"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoling Deng","raw_affiliation_strings":["College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5588-3443","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101666108","display_name":"Yubin Lan","orcid":"https://orcid.org/0000-0001-6664-5571"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Lan","raw_affiliation_strings":["College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6664-5571","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773959","display_name":"Yongbing Long","orcid":"https://orcid.org/0000-0001-7956-8173"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongbing Long","raw_affiliation_strings":["College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7956-8173","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, College of Artificial Intelligence, National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Engineering Technology Research Center of Smart Agriculture, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082041657","display_name":"Jian Weng","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Weng","raw_affiliation_strings":["College of Cyber Security, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4067-8230","affiliations":[{"raw_affiliation_string":"College of Cyber Security, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062494507","display_name":"Zhiquan Liu","orcid":"https://orcid.org/0000-0002-3934-2177"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Liu","raw_affiliation_strings":["College of Cyber Security, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3934-2177","affiliations":[{"raw_affiliation_string":"College of Cyber Security, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Cloud BU, Huawei Technologies, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7252-5047","affiliations":[{"raw_affiliation_string":"Cloud BU, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100633270"],"corresponding_institution_ids":["https://openalex.org/I101479585"],"apc_list":null,"apc_paid":null,"fwci":1.8242,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88333362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"46","issue":"2","first_page":"851","last_page":"868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9979000091552734,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9228000044822693,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12439","display_name":"Dental Research and COVID-19","score":0.9053999781608582,"subfield":{"id":"https://openalex.org/subfields/3500","display_name":"General Dentistry"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7446486949920654},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7312201261520386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7051604390144348},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6339227557182312},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5625083446502686},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5483645796775818},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48338499665260315},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.45932361483573914},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4523523449897766},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.41776689887046814},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38951820135116577},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3240676522254944}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7446486949920654},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7312201261520386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7051604390144348},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6339227557182312},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5625083446502686},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5483645796775818},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48338499665260315},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.45932361483573914},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4523523449897766},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.41776689887046814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38951820135116577},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3240676522254944},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3325533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3325533","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:37851556","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37851556","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/G1898902296","display_name":null,"funder_award_id":"32371984","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3598806485","display_name":null,"funder_award_id":"2019A1515011276","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G4595791608","display_name":null,"funder_award_id":"61906074","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W64897123","https://openalex.org/W652269744","https://openalex.org/W1536680647","https://openalex.org/W1797268635","https://openalex.org/W1821462560","https://openalex.org/W2044913453","https://openalex.org/W2070148066","https://openalex.org/W2098411764","https://openalex.org/W2109317801","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2289084343","https://openalex.org/W2328434568","https://openalex.org/W2334493732","https://openalex.org/W2400717490","https://openalex.org/W2479109623","https://openalex.org/W2533598788","https://openalex.org/W2596142952","https://openalex.org/W2604961537","https://openalex.org/W2618530766","https://openalex.org/W2737725206","https://openalex.org/W2739879705","https://openalex.org/W2773003563","https://openalex.org/W2887567284","https://openalex.org/W2924476266","https://openalex.org/W2948162522","https://openalex.org/W2962716320","https://openalex.org/W2963037989","https://openalex.org/W2963283377","https://openalex.org/W2963407932","https://openalex.org/W2963499153","https://openalex.org/W2963538198","https://openalex.org/W2963545832","https://openalex.org/W2963779825","https://openalex.org/W2963955422","https://openalex.org/W2963960318","https://openalex.org/W2964016283","https://openalex.org/W2965373098","https://openalex.org/W2979571231","https://openalex.org/W2982234480","https://openalex.org/W2982407353","https://openalex.org/W2986692991","https://openalex.org/W2990947836","https://openalex.org/W2991221721","https://openalex.org/W2991813857","https://openalex.org/W2998708909","https://openalex.org/W3022216559","https://openalex.org/W3034359780","https://openalex.org/W3034379915","https://openalex.org/W3035297600","https://openalex.org/W3035655772","https://openalex.org/W3089741414","https://openalex.org/W3096741441","https://openalex.org/W3097309192","https://openalex.org/W3109728025","https://openalex.org/W3143107425","https://openalex.org/W3171926364","https://openalex.org/W4225641084","https://openalex.org/W4304084141","https://openalex.org/W4312791158","https://openalex.org/W6638319203","https://openalex.org/W6638523607","https://openalex.org/W6678470764","https://openalex.org/W6682222085","https://openalex.org/W6682691769","https://openalex.org/W6742888842","https://openalex.org/W6754700304","https://openalex.org/W6767354860"],"related_works":["https://openalex.org/W4214877189","https://openalex.org/W2074502265","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2366718574","https://openalex.org/W2905271011","https://openalex.org/W3164948662","https://openalex.org/W4289536128","https://openalex.org/W3153597579","https://openalex.org/W1872833176"],"abstract_inverted_index":{"Zero-shot":[0],"learning":[1,41],"(ZSL)":[2],"aims":[3,130,168],"to":[4,65,77,97,101,131,140,160,169],"recognize":[5],"objects":[6],"from":[7,15],"unseen":[8,32],"classes":[9],"only":[10],"based":[11,88],"on":[12,23,89,176],"labeled":[13],"images":[14],"seen":[16],"classes.":[17],"Most":[18],"existing":[19],"ZSL":[20,37,195],"methods":[21],"focus":[22],"optimizing":[24],"feature":[25,47,91,158],"spaces":[26,48],"or":[27],"generating":[28],"visual":[29,57,112,135,153],"features":[30,58,113,163],"of":[31,148],"classes,":[33],"both":[34,149,193],"in":[35,72,192],"conventional":[36,194],"and":[38,59,80,151,180,196],"generalized":[39],"zero-shot":[40],"(GZSL).":[42],"However,":[43],"since":[44],"the":[45,106,118,190],"learned":[46],"are":[49,62,143],"suboptimal,":[50],"there":[51],"exists":[52],"many":[53],"virtual":[54,70,119],"connections":[55,120],"where":[56],"semantic":[60,116],"attributes":[61,138],"not":[63],"corresponding":[64],"each":[66],"other.":[67],"To":[68,145],"reduce":[69],"connections,":[71],"this":[73],"paper,":[74],"we":[75,155],"propose":[76],"discover":[78],"comprehensive":[79,111],"fine-grained":[81,134],"object":[82,95,108],"parts":[83,96,109],"by":[84,124],"building":[85],"explanatory":[86],"graphs":[87],"convolutional":[90],"maps,":[92],"then":[93],"aggregate":[94],"train":[98],"a":[99,125,157,165],"part-net":[100,129],"obtain":[102],"prediction":[103],"results.":[104],"Since":[105,128],"aggregated":[107],"contain":[110],"for":[114],"activating":[115],"attributes,":[117],"can":[121],"be":[122],"reduced":[123],"large":[126],"extent.":[127],"extract":[132,170],"local":[133,150,162],"features,":[136,154],"some":[137],"related":[139],"global":[141,152,171],"structures":[142],"ignored.":[144],"take":[146],"advantage":[147],"design":[156],"distiller":[159],"distill":[161],"into":[164],"master-net":[166],"which":[167],"features.":[172],"The":[173],"experimental":[174],"results":[175],"AWA2,":[177],"CUB,":[178],"FLO,":[179],"SUN":[181],"dataset":[182],"demonstrate":[183],"that":[184],"our":[185],"proposed":[186],"method":[187],"obviously":[188],"outperforms":[189],"state-of-the-arts":[191],"GZSL":[197],"tasks.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}