QR-Code

GAGAN: Enhancing Image Generation Through Hybrid Optimization of Genetic Algorithms and Deep Convolutional Generative Adversarial Networks

Generative Adversarial Networks (GANs) are highly effective for generating realistic images, yet their training can be unstable due to challenges such as mode collapse and oscillatory convergence. In this paper, we propose a novel hybrid optimization method that integrates Genetic Algorithms (GAs) t...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Despoina Konstantopoulou, Paraskevi Zacharia, Michail Papoutsidakis, Helen C. Leligou, Charalampos Patrikakis
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-12-01
Schriftenreihe:Algorithms
Schlagworte:
image generation
generative AI
genetic algorithms
deep convolutional generative adversarial networks
discriminator weight optimization
Online-Zugang:https://www.mdpi.com/1999-4893/17/12/584
Tags: Tag hinzufügen
Keine Tags, Fügen Sie das erste Tag hinzu!

Ähnliche Einträge