{"id":"https://openalex.org/W3011907409","doi":"https://doi.org/10.1109/mis.2020.2979835","title":"VSE-fs: Fast Full-Sample Visual Semantic Embedding","display_name":"VSE-fs: Fast Full-Sample Visual Semantic Embedding","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3011907409","doi":"https://doi.org/10.1109/mis.2020.2979835","mag":"3011907409"},"language":"en","primary_location":{"id":"doi:10.1109/mis.2020.2979835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.2979835","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Intelligent Systems","raw_type":"journal-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/A5032897354","display_name":"Songlin Zhai","orcid":"https://orcid.org/0000-0003-2666-9952"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Songlin Zhai","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007061198","display_name":"Guibing Guo","orcid":"https://orcid.org/0000-0002-1709-5056"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guibing Guo","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081665927","display_name":"Fajie Yuan","orcid":"https://orcid.org/0000-0001-8452-9929"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fajie Yuan","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390839","display_name":"Yuan Liu","orcid":"https://orcid.org/0000-0002-0246-0778"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Liu","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326915","display_name":"Xingwei Wang","orcid":"https://orcid.org/0000-0003-2856-4716"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingwei Wang","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032897354"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02633431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"4","first_page":"3","last_page":"12"},"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9995999932289124,"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":0.9988999962806702,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8676944971084595},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.804443359375},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.564167857170105},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5265696048736572},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.47124868631362915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45308271050453186},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4232941269874573},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.41079413890838623},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3665064871311188},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35021018981933594},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3332495093345642},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2447710931301117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8676944971084595},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.804443359375},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.564167857170105},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5265696048736572},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.47124868631362915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45308271050453186},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4232941269874573},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.41079413890838623},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3665064871311188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35021018981933594},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3332495093345642},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2447710931301117},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mis.2020.2979835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.2979835","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4591949316","display_name":null,"funder_award_id":"N181705007","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5219054260","display_name":null,"funder_award_id":"61772125","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8828627166","display_name":null,"funder_award_id":"61702084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G983970540","display_name":null,"funder_award_id":"61702090","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W2006147162","https://openalex.org/W2007972815","https://openalex.org/W2097117768","https://openalex.org/W2152808281","https://openalex.org/W2153579005","https://openalex.org/W2162867699","https://openalex.org/W2340502990","https://openalex.org/W2782368579","https://openalex.org/W2963161823","https://openalex.org/W4294170691","https://openalex.org/W6600827882","https://openalex.org/W6682691769","https://openalex.org/W6747126320"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W2042102171"],"abstract_inverted_index":{"The":[0,121],"visual":[1,13],"semantic":[2,16],"embedding":[3,10],"(VSE)":[4],"aims":[5],"to":[6,35,55,91,111],"construct":[7],"a":[8,25,62],"joint":[9],"space":[11],"between":[12],"features":[14],"and":[15,41,115],"information,":[17],"whereby":[18],"classes":[19,67],"can":[20],"be":[21],"well":[22],"retrieved":[23],"for":[24],"given":[26],"image.":[27],"However,":[28,72],"VSE":[29,93],"faces":[30],"the":[31,36,42,66,80,85,98,138],"computational":[32],"challenge":[33],"due":[34],"large":[37],"scale":[38],"image-class":[39],"data":[40,87],"constrained":[43],"system":[44],"processing":[45],"power.":[46],"To":[47],"speed":[48],"up":[49],"model":[50],"training,":[51],"many":[52],"researchers":[53],"resort":[54],"different":[56],"sampling":[57,81,140],"strategies":[58,110],"by":[59],"involving":[60],"only":[61,133],"small":[63],"portion":[64],"of":[65],"at":[68],"each":[69],"training":[70],"step.":[71],"these":[73],"methods":[74],"are":[75],"greatly":[76],"biased":[77],"especially":[78],"when":[79],"distribution":[82],"deviates":[83],"from":[84],"true":[86],"distribution.":[88],"In":[89],"order":[90],"retain":[92],"models":[94],"fidelity,":[95],"we":[96],"adopt":[97],"regular":[99],"full-sample":[100],"in":[101],"our":[102,130],"algorithm.":[103],"We":[104],"also":[105,143],"devise":[106],"two":[107],"separate":[108],"optimization":[109],"reduce":[112],"time":[113],"complexity,":[114],"derive":[116],"more":[117,145],"effective":[118],"updating":[119],"rules.":[120],"experimental":[122],"results":[123],"on":[124],"four":[125],"real":[126],"datasets":[127],"demonstrate":[128],"that":[129],"approach":[131],"not":[132],"converges":[134],"much":[135],"faster":[136],"than":[137],"state-of-the-art":[139],"models,":[141],"but":[142],"generates":[144],"accurate":[146],"class":[147],"retrieval.":[148]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}