Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6183
Title: AN ALGORITHM FOR GENERATING DESCRIPTIVE SENTENCES OF THE HUMAN HEAD PARTS BASED ON ENGLISH GRAMMAR
Authors: Alamro, Loai 
Yusof, Yuhanis 
Yusoff, Nooraini 
Keywords: Deep Learning;Human Attribute Classification;Human Attribute Description
Issue Date: 2024
Publisher: Little Lion Scientific
Journal: Journal of Theoretical and Applied Information Technology 
Abstract: 
Human 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.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/6183
ISSN: 19928645
Appears in Collections:Faculty of Data Science and Computing - Journal (Scopus/WOS)

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