Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6183
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dc.contributor.authorAlamro, Loaien_US
dc.contributor.authorYusof, Yuhanisen_US
dc.contributor.authorYusoff, Noorainien_US
dc.date.accessioned2024-07-18T02:30:43Z-
dc.date.available2024-07-18T02:30:43Z-
dc.date.issued2024-
dc.identifier.issn19928645-
dc.identifier.urihttp://hdl.handle.net/123456789/6183-
dc.descriptionScopusen_US
dc.description.abstractHuman head exhibits many biological features (attributes) that represent the characteristics of the human head with robust inherent stability and individual variation. These attributes provide important discriminative knowledge about humans, such as gender, age, race, hairstyle, hair color, etc. Recently, several human head attribute classification networks have been proposed. However, these networks do not provide a clear picture of the human head because they predict head attributes in terms of binary values (i.e., 0 or 1) or by their labels (i.e., male, young). Therefore, in this study, a description algorithm was proposed to describe the main characteristics of the human head using the adjective’s arrangement rules. The proposed algorithm was reviewed by experts, and the responses of seven experts show that the algorithm follows the adjective’s arrangement rules in accordance with the conventions of human language. The experts also found the descriptive sentences acceptable, understandable, and grammatically correct.en_US
dc.publisherLittle Lion Scientificen_US
dc.relation.ispartofJournal of Theoretical and Applied Information Technologyen_US
dc.subjectDeep Learningen_US
dc.subjectHuman Attribute Classificationen_US
dc.subjectHuman Attribute Descriptionen_US
dc.titleAN ALGORITHM FOR GENERATING DESCRIPTIVE SENTENCES OF THE HUMAN HEAD PARTS BASED ON ENGLISH GRAMMARen_US
dc.typeInternationalen_US
dc.description.page2945 - 295315en_US
dc.volume102(7)en_US
dc.description.typeArticleen_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeInternational-
crisitem.author.deptUniversiti Malaysia Kelantan-
crisitem.author.orcid0000-0003-2703-2531-
Appears in Collections:Faculty of Data Science and Computing - Journal (Scopus/WOS)
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