Improving Road Semantic Segmentation Using Generative Adversarial Network

Improving Road Semantic Segmentation Using Generative Adversarial Network

Road network extraction from remotely sensed imagery has become a powerful tool for updating geospatial databases, owing to the success of convolutional neural network (CNN) based deep learning semantic segmentation techniques combined with the high-resolution imagery that modern remote sensing prov...

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Bibliographic Details
Main Authors: Abolfazl Abdollahi, Biswajeet Pradhan, Gaurav Sharma, Khairul Nizam Abdul Maulud, Abdullah Alamri
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
GAN
road segmentation
remote sensing
deep learning
U-Net
Online Access:https://ieeexplore.ieee.org/document/9416669/

Internet

https://ieeexplore.ieee.org/document/9416669/

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