IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images

IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images

Automatic extraction of buildings from High-Resolution Remote Sensing (RS) Imagery is of great practical interest for numerous applications; including urban planning, change detection, disaster management, estimation of human population, and many other geospatial related applications. This paper pro...

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Bibliographic Details
Main Authors: Md. Abdul Alim Sheikh, Tanmoy Maity, Alok Kole
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Building extraction
deep learning
encoder-decoder network
atrous spatial pyramid pooling
remote sensing imagery
cross-entropy and dice loss
Online Access:https://ieeexplore.ieee.org/document/9748124/

Internet

https://ieeexplore.ieee.org/document/9748124/

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