{"id":"https://openalex.org/W2945813800","doi":"https://doi.org/10.1109/icip.2019.8803458","title":"Learning Visually Consistent Label Embeddings for Zero-Shot Learning","display_name":"Learning Visually Consistent Label Embeddings for Zero-Shot Learning","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2945813800","doi":"https://doi.org/10.1109/icip.2019.8803458","mag":"2945813800"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803458","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.06764","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063169881","display_name":"Berkan Demirel","orcid":"https://orcid.org/0000-0002-5759-6410"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Berkan Demirel","raw_affiliation_strings":["HAVELSAN Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HAVELSAN Inc","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051499142","display_name":"Ramazan G\u00f6kberk Cinbi\u015f","orcid":"https://orcid.org/0000-0003-0962-7101"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ramazan Gokberk Cinbis","raw_affiliation_strings":["Middle East Technical University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Middle East Technical University","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090096127","display_name":"Nazl\u0131 \u0130kizler-Cinbi\u015f","orcid":"https://orcid.org/0000-0002-8644-2875"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Nazli Ikizler-Cinbis","raw_affiliation_strings":["Hacettepe University","hacettepe university"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hacettepe University","institution_ids":["https://openalex.org/I66514158"]},{"raw_affiliation_string":"hacettepe university","institution_ids":["https://openalex.org/I66514158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3656","last_page":"3660"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9918000102043152,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9539999961853027,"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/embedding","display_name":"Embedding","score":0.7865185737609863},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7267103791236877},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6998679637908936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6832834482192993},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.6021468043327332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5893623232841492},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5583914518356323},{"id":"https://openalex.org/keywords/vector-space","display_name":"Vector space","score":0.5375027656555176},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.4779800772666931},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3853319585323334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36882543563842773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2531643509864807},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05556783080101013}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7865185737609863},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7267103791236877},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6998679637908936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6832834482192993},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.6021468043327332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5893623232841492},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5583914518356323},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.5375027656555176},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.4779800772666931},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3853319585323334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36882543563842773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2531643509864807},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05556783080101013},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2019.8803458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803458","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.06764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.06764","pdf_url":"https://arxiv.org/pdf/1905.06764","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.1905.06764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1905.06764","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2945813800","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1905.06764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.06764","pdf_url":"https://arxiv.org/pdf/1905.06764","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.699999988079071,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2945813800.pdf","grobid_xml":"https://content.openalex.org/works/W2945813800.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W93016980","https://openalex.org/W2005285092","https://openalex.org/W2037227137","https://openalex.org/W2044913453","https://openalex.org/W2077071968","https://openalex.org/W2098411764","https://openalex.org/W2102765684","https://openalex.org/W2109317801","https://openalex.org/W2123024445","https://openalex.org/W2128532956","https://openalex.org/W2134270519","https://openalex.org/W2145215286","https://openalex.org/W2153579005","https://openalex.org/W2169738563","https://openalex.org/W2250539671","https://openalex.org/W2289084343","https://openalex.org/W2334493732","https://openalex.org/W2441043183","https://openalex.org/W2552383788","https://openalex.org/W2744242754","https://openalex.org/W2746797088","https://openalex.org/W2748075849","https://openalex.org/W2748618181","https://openalex.org/W2762085884","https://openalex.org/W2887567284","https://openalex.org/W2898502605","https://openalex.org/W2962714319","https://openalex.org/W2963465381","https://openalex.org/W2963486920","https://openalex.org/W2963545832","https://openalex.org/W2963846885","https://openalex.org/W2964086552","https://openalex.org/W2964121744","https://openalex.org/W3100093508","https://openalex.org/W3106051827","https://openalex.org/W3143107425","https://openalex.org/W6603820874","https://openalex.org/W6631190155","https://openalex.org/W6678470764","https://openalex.org/W6682691769","https://openalex.org/W6754073506"],"related_works":["https://openalex.org/W2970389836","https://openalex.org/W2940957522","https://openalex.org/W2991391395","https://openalex.org/W2917742317","https://openalex.org/W3111733255","https://openalex.org/W2951445760","https://openalex.org/W2952647681","https://openalex.org/W2950716832","https://openalex.org/W3088406982","https://openalex.org/W2963538198","https://openalex.org/W2965590994","https://openalex.org/W2997701591","https://openalex.org/W2994234078","https://openalex.org/W2964086552","https://openalex.org/W2784407971","https://openalex.org/W2923124246","https://openalex.org/W2883124384","https://openalex.org/W2997918867","https://openalex.org/W2998124234","https://openalex.org/W2623164477"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"propose":[4],"a":[5],"zero-shot":[6],"learning":[7,18],"method":[8,91],"to":[9,35,71],"effectively":[10],"model":[11,26,70],"knowledge":[12],"transfer":[13],"between":[14],"classes":[15,45,57],"via":[16],"jointly":[17],"visually":[19],"consistent":[20],"word":[21,40,52],"vectors":[22,41,65],"and":[23,44,61,84],"label":[24],"embedding":[25,69],"in":[27,66,95],"an":[28],"end-to-end":[29],"manner.":[30],"The":[31],"main":[32],"idea":[33],"is":[34],"project":[36],"the":[37,47,63,67,77,85],"vector":[38],"space":[39,49],"of":[42,54],"attributes":[43],"into":[46],"visual":[48],"such":[50],"that":[51,89],"representations":[53],"semantically":[55],"related":[56],"become":[58],"more":[59],"closer,":[60],"use":[62],"projected":[64],"proposed":[68,78],"identify":[72],"unseen":[73],"classes.":[74],"We":[75],"evaluate":[76],"approach":[79],"on":[80],"two":[81],"benchmark":[82],"datasets":[83],"experimental":[86],"results":[87],"show":[88],"our":[90],"yields":[92],"significant":[93],"improvements":[94],"recognition":[96],"accuracy.":[97]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}