{"id":"https://openalex.org/W2100031962","doi":"https://doi.org/10.1007/978-3-319-46478-7_5","title":"Learning Visual Features from Large Weakly Supervised Data","display_name":"Learning Visual Features from Large Weakly Supervised Data","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2100031962","doi":"https://doi.org/10.1007/978-3-319-46478-7_5","mag":"2100031962"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-46478-7_5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-46478-7_5","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5107859338","display_name":"Armand Joulin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Armand Joulin","raw_affiliation_strings":["Facebook AI Research, New York, USA"],"affiliations":[{"raw_affiliation_string":"Facebook AI Research, New York, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109065097","display_name":"Laurens van der Maaten","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laurens van der Maaten","raw_affiliation_strings":["Facebook AI Research, New York, USA"],"affiliations":[{"raw_affiliation_string":"Facebook AI Research, New York, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081649142","display_name":"Allan Jabri","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Allan Jabri","raw_affiliation_strings":["Facebook AI Research, New York, USA"],"affiliations":[{"raw_affiliation_string":"Facebook AI Research, New York, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017292577","display_name":"Nicolas Vasilache","orcid":"https://orcid.org/0000-0002-4096-3325"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicolas Vasilache","raw_affiliation_strings":["Facebook AI Research, New York, USA"],"affiliations":[{"raw_affiliation_string":"Facebook AI Research, New York, USA","institution_ids":["https://openalex.org/I4210114444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107859338"],"corresponding_institution_ids":["https://openalex.org/I4210114444"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":12.8838,"has_fulltext":false,"cited_by_count":315,"citation_normalized_percentile":{"value":0.9870801,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.8847370147705078},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.652579665184021},{"id":"https://openalex.org/keywords/pace","display_name":"Pace","score":0.6003332138061523},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.552864134311676},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4957796037197113},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4519861936569214},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4177522659301758},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4135345220565796},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41270673274993896},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30679816007614136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8847370147705078},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.652579665184021},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.6003332138061523},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.552864134311676},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4957796037197113},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4519861936569214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4177522659301758},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4135345220565796},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41270673274993896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30679816007614136},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-46478-7_5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-46478-7_5","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W36903255","https://openalex.org/W68733909","https://openalex.org/W101201821","https://openalex.org/W203719604","https://openalex.org/W603908379","https://openalex.org/W1558797106","https://openalex.org/W1590105591","https://openalex.org/W1845277745","https://openalex.org/W1858383477","https://openalex.org/W1861492603","https://openalex.org/W1875842236","https://openalex.org/W1897761818","https://openalex.org/W1921293667","https://openalex.org/W1933349210","https://openalex.org/W1938167356","https://openalex.org/W1976921161","https://openalex.org/W1977500159","https://openalex.org/W1981276685","https://openalex.org/W1987063155","https://openalex.org/W1987549167","https://openalex.org/W1996140089","https://openalex.org/W1997454659","https://openalex.org/W2017814585","https://openalex.org/W2018573225","https://openalex.org/W2031342017","https://openalex.org/W2037227137","https://openalex.org/W2038765747","https://openalex.org/W2062118960","https://openalex.org/W2064675550","https://openalex.org/W2070753207","https://openalex.org/W2081613070","https://openalex.org/W2097117768","https://openalex.org/W2097732278","https://openalex.org/W2100714283","https://openalex.org/W2102605133","https://openalex.org/W2107698128","https://openalex.org/W2108598243","https://openalex.org/W2109586012","https://openalex.org/W2115752676","https://openalex.org/W2117539524","https://openalex.org/W2120725344","https://openalex.org/W2122528955","https://openalex.org/W2123024445","https://openalex.org/W2124219775","https://openalex.org/W2134670479","https://openalex.org/W2137735870","https://openalex.org/W2145056192","https://openalex.org/W2146223937","https://openalex.org/W2152161678","https://openalex.org/W2152790380","https://openalex.org/W2161381512","https://openalex.org/W2162950292","https://openalex.org/W2163605009","https://openalex.org/W2164587673","https://openalex.org/W2169393274","https://openalex.org/W2171361956","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2202226326","https://openalex.org/W2250384498","https://openalex.org/W2259472270","https://openalex.org/W2533598788","https://openalex.org/W2602753196","https://openalex.org/W2949194345","https://openalex.org/W2950276680","https://openalex.org/W2950577311","https://openalex.org/W2950761309","https://openalex.org/W2953236957","https://openalex.org/W2953276893","https://openalex.org/W2962835968","https://openalex.org/W2963932686","https://openalex.org/W4234552385","https://openalex.org/W6604344240","https://openalex.org/W6830475188"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4380075502","https://openalex.org/W4291897433","https://openalex.org/W4223943233"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":35},{"year":2021,"cited_by_count":51},{"year":2020,"cited_by_count":44},{"year":2019,"cited_by_count":40},{"year":2018,"cited_by_count":28},{"year":2017,"cited_by_count":35},{"year":2016,"cited_by_count":13}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}