Classification of Very High-Resolution Remote Sensing Imagery Using a Fully Convolutional Network With Global and Local Context Information Enhancements

Classification of Very High-Resolution Remote Sensing Imagery Using a Fully Convolutional Network With Global and Local Context Information Enhancements

Deep learning methods for semantic image segmentation can effectively extract geographical features from very high-resolution (VHR) remote sensing images. However, these methods experience over-segmentation in low-level features and a breakdown in the integrity of objects with fixed patch sizes due...

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Bibliographic Details
Main Authors: Huanjun Hu, Zheng Li, Lin Li, Hui Yang, Haihong Zhu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Attention mechanism
DenseNet
semantic segmentation
very high-resolution remote sensing images
Online Access:https://ieeexplore.ieee.org/document/8952711/

Internet

https://ieeexplore.ieee.org/document/8952711/

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