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

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