Enhanced Hyper-Parameter Of Semi-Supervised Generative Adversarial Networks Based On Sine Cosine Algorithm For Multimedia Datasets

Saleh Al-Ragehi, Anas Abdo Saleh (2022) Enhanced Hyper-Parameter Of Semi-Supervised Generative Adversarial Networks Based On Sine Cosine Algorithm For Multimedia Datasets. Masters thesis, Universiti Teknologi PETRONAS.

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Abstract

Generative Adversarial Networks (GANs) are neural networks that allow models to learn deep representations without requiring a large amount of training data.

Item Type:	Thesis (Masters)
Subjects:	T Technology > T Technology (General)
Departments / MOR / COE:	Engineering > Information Technology
Depositing User:	Mr Ahmad Suhairi Mohamed Lazim
Date Deposited:	14 Sep 2023 08:40
Last Modified:	14 Sep 2023 08:40
URI:	http://utpedia.utp.edu.my/id/eprint/24949

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