Multi-Class Guided GAN for Remote-Sensing Image Synthesis Based on Semantic Labels

Multi-Class Guided GAN for Remote-Sensing Image Synthesis Based on Semantic Labels

In the scenario of limited labeled remote-sensing datasets, the model’s performance is constrained by the insufficient availability of data. Generative model-based data augmentation has emerged as a promising solution to this limitation. While existing generative models perform well in natural scene...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhenye Niu, Yuxia Li, Yushu Gong, Bowei Zhang, Yuan He, Jinglin Zhang, Mengyu Tian, Lei He
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
remote-sensing images
generative adversarial networks
image synthesis
data augmentation
Online Access:https://www.mdpi.com/2072-4292/17/2/344
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items