BiFDANet: Unsupervised Bidirectional Domain Adaptation for Semantic Segmentation of Remote Sensing Images

BiFDANet: Unsupervised Bidirectional Domain Adaptation for Semantic Segmentation of Remote Sensing Images

When segmenting massive amounts of remote sensing images collected from different satellites or geographic locations (cities), the pre-trained deep learning models cannot always output satisfactory predictions. To deal with this issue, domain adaptation has been widely utilized to enhance the genera...

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Bibliographic Details
Main Authors: Yuxiang Cai, Yingchun Yang, Qiyi Zheng, Zhengwei Shen, Yongheng Shang, Jianwei Yin, Zhongtian Shi
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Remote Sensing
Subjects:
unsupervised domain adaptation
bidirectional domain adaptation
convolutional neural networks (CNNs)
image-to-image translation
generative adversarial networks (GANs)
remote sensing images
Online Access:https://www.mdpi.com/2072-4292/14/1/190

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