Unsupervised Domain Adaptation Using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

Unsupervised Domain Adaptation Using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

Segmenting aerial images is of great potential in surveillance and scene understanding of urban areas. It provides a mean for automatic reporting of the different events that happen in inhabited areas. This remarkably promotes public safety and traffic management applications. After the wide adoptio...

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Bibliographic Details
Main Authors: Bilel Benjdira, Yakoub Bazi, Anis Koubaa, Kais Ouni
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Remote Sensing
Subjects:
convolutional neural networks
semantic segmentation
aerial imagery
domain adaptation
gener ative adversarial networks
Online Access:https://www.mdpi.com/2072-4292/11/11/1369

Internet

https://www.mdpi.com/2072-4292/11/11/1369

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