Show simple item record

HFM: A Hybrid Feature Model Based on Conditional Auto Encoders for Zero-Shot Learning

dc.contributor.authorAl Machot, Fadi
dc.contributor.authorUllah, Mohib
dc.contributor.authorUllah, Habib
dc.date.accessioned2023-06-06T10:22:05Z
dc.date.available2023-06-06T10:22:05Z
dc.date.created2022-09-22T13:33:34Z
dc.date.issued2022
dc.identifier.citationJournal of Imaging. 2022, 8 (6), .
dc.identifier.issn2313-433X
dc.identifier.urihttps://hdl.handle.net/11250/3070099
dc.language.isoeng
dc.titleHFM: A Hybrid Feature Model Based on Conditional Auto Encoders for Zero-Shot Learning
dc.title.alternativeHFM: A Hybrid Feature Model Based on Conditional Auto Encoders for Zero-Shot Learning
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber0
dc.source.volume8
dc.source.journalJournal of Imaging
dc.source.issue6
dc.identifier.doi10.3390/jimaging8060171
dc.identifier.cristin2054356
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Files in this item

Thumbnail
Name:
jimaging-08-00171.pdf
Size:
944.3Kb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record