Realistic River Image Synthesis Using Deep Generative Adversarial Networks

Realistic River Image Synthesis Using Deep Generative Adversarial Networks

In this paper, we demonstrated a practical application of realistic river image generation using deep learning. Specifically, we explored a generative adversarial network (GAN) model capable of generating high-resolution and realistic river images that can be used to support modeling and analysis in...

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Bibliographic Details
Main Authors: Akshat Gautam, Muhammed Sit, Ibrahim Demir
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-02-01
Series:Frontiers in Water
Subjects:
generative adversarial networks
deep learning
river image
imagery synthesis
hydrological datasets
Online Access:https://www.frontiersin.org/articles/10.3389/frwa.2022.784441/full

Internet

https://www.frontiersin.org/articles/10.3389/frwa.2022.784441/full

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