{"id":"https://openalex.org/W4318256792","doi":"https://doi.org/10.1145/3570236.3570237","title":"Zero-shot Hand-held Objects Recognition Based on Global Feature Relationships","display_name":"Zero-shot Hand-held Objects Recognition Based on Global Feature Relationships","publication_year":2022,"publication_date":"2022-09-29","ids":{"openalex":"https://openalex.org/W4318256792","doi":"https://doi.org/10.1145/3570236.3570237"},"language":"en","primary_location":{"id":"doi:10.1145/3570236.3570237","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3570236.3570237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Intelligent Information Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5079877650","display_name":"Minghui Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minghui Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0000-0003-1646-876X","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036505077","display_name":"Lizong Zhang","orcid":"https://orcid.org/0000-0002-0719-9556"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizong Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0000-0002-0719-9556","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062758957","display_name":"Yiying Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiying Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0000-0002-0172-8373","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090319362","display_name":"Xiujian Zhang","orcid":"https://orcid.org/0000-0001-5656-0419"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiujian Zhang","raw_affiliation_strings":["Beijing Aerospace Institute for Metrology and Measurement Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-5656-0419","affiliations":[{"raw_affiliation_string":"Beijing Aerospace Institute for Metrology and Measurement Technology, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003393482","display_name":"Guisong Liu","orcid":"https://orcid.org/0000-0003-2360-0466"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guisong Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0000-0003-2360-0466","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079877650"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14649786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"04474","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9965999722480774,"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":0.9965999722480774,"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":0.9941999912261963,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9869999885559082,"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/mobile-device","display_name":"Mobile device","score":0.7695541381835938},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7615087032318115},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6057416200637817},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.583034336566925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5716421604156494},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5617567300796509},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5355939865112305},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4966462254524231},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48673275113105774},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48033562302589417},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4771023392677307},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4280989170074463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41862937808036804},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1724347472190857},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10402852296829224},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09964179992675781}],"concepts":[{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.7695541381835938},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615087032318115},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6057416200637817},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.583034336566925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5716421604156494},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5617567300796509},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5355939865112305},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4966462254524231},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48673275113105774},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48033562302589417},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4771023392677307},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4280989170074463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41862937808036804},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1724347472190857},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10402852296829224},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09964179992675781},{"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/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":1,"locations":[{"id":"doi:10.1145/3570236.3570237","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3570236.3570237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Intelligent Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2108598243","https://openalex.org/W2154851992","https://openalex.org/W2250539671","https://openalex.org/W2963037989","https://openalex.org/W2963486920","https://openalex.org/W3104097132","https://openalex.org/W4231290138","https://openalex.org/W4234552385","https://openalex.org/W4236965008","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"there":[3],"have":[4],"been":[5],"frequent":[6],"terrorist":[7],"attacks":[8],"both":[9],"at":[10],"home":[11],"and":[12,64,104],"abroad.":[13],"Accurate":[14],"detection":[15],"of":[16,20,36,77],"a":[17,24,46,65],"wide":[18],"variety":[19],"handheld":[21,37,40,125],"objects":[22],"is":[23],"problem":[25],"that":[26,56,114],"needs":[27],"an":[28,60],"urgent":[29],"solution.":[30],"To":[31],"better":[32],"exploit":[33],"the":[34,74,78,83,101,106,119],"effects":[35],"movements":[38],"on":[39,52,100],"object":[41,49,126],"recognition,":[42],"this":[43,115],"paper":[44],"proposes":[45],"zero-shot":[47],"hand-held":[48],"recognition":[50,120,127],"based":[51],"global":[53],"feature":[54],"relations":[55,67,88],"comprise":[57],"two":[58],"modules:":[59],"image":[61,70,80],"processing":[62,71],"module":[63,72,89],"semantic":[66,87,94],"module.":[68],"The":[69,86],"learns":[73],"visual":[75],"classifier":[76],"input":[79],"to":[81,123],"obtain":[82],"classification":[84,107],"weights.":[85],"propagates":[90],"structural":[91],"knowledge":[92,102],"through":[93,96],"learning":[95],"graph":[97,103],"convolution":[98],"operations":[99],"obtains":[105],"weights":[108],"for":[109],"all":[110],"categories.":[111],"Results":[112],"indicate":[113],"method":[116],"significantly":[117],"improves":[118],"rate":[121],"compared":[122],"traditional":[124],"methods.":[128]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
