A deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples

A deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples

Wetlands have long been recognized among the most critical ecosystems globally, yet their numbers quickly diminish due to human activities and climate change. Thus, large-scale wetland monitoring is essential to provide efficient spatial and temporal insights for resource management and conservation...

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Bibliographic Details
Main Authors: Ali Jamali, Masoud Mahdianpari, Fariba Mohammadimanesh, Saeid Homayouni
Format: Article
Language:English
Published: Elsevier 2022-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Generative adversarial network
Convolutional neural network
Wetland classification
New Brunswick
Vision Transformer (ViT)
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843222002837

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http://www.sciencedirect.com/science/article/pii/S1569843222002837

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