Building Footprint Extraction From VHR Remote Sensing Images Combined With Normalized DSMs Using Fused Fully Convolutional Networks

Building Footprint Extraction From VHR Remote Sensing Images Combined With Normalized DSMs Using Fused Fully Convolutional Networks

Automatic building extraction and delineation from high-resolution satellite imagery is an important but very challenging task, due to the extremely large diversity of building appearances. Nowadays, it is possible to use multiple high-resolution remote sensing data sources, which allow the integrat...

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Bibliographic Details
Main Authors: Ksenia Bittner, Fathalrahman Adam, Shiyong Cui, Marco Korner, Peter Reinartz
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Binary classification
building footprint
data fusion
deep learning
fully convolutional networks (FCNs)
satellite images
Online Access:https://ieeexplore.ieee.org/document/8447548/

Internet

https://ieeexplore.ieee.org/document/8447548/

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