Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data

Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data

Automatic building extraction has been applied in many domains. It is also a challenging problem because of the complex scenes and multiscale. Deep learning algorithms, especially fully convolutional neural networks (FCNs), have shown robust feature extraction ability than traditional remote sensing...

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Bibliographic Details
Main Authors: Qinglie Yuan, Helmi Zulhaidi Mohd Shafri, Aidi Hizami Alias, Shaiful Jahari bin Hashim
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
building extraction
multiscale feature fusion
deep learning
convolution neural network
semantic segmentation
Online Access:https://www.mdpi.com/2072-4292/13/13/2473

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