Boundary-Aware Dual-Stream Network for VHR Remote Sensing Images Semantic Segmentation
Semantic segmentation for very-high-resolution remote sensing images has been a research hotspot in the field of remote sensing image analysis. However, most existing methods still suffer from a challenge that object boundaries cannot be finely recovered. To tackle the problem, we develop a dual-str...
Main Authors: | Zhixian Nong, Xin Su, Yi Liu, Zongqian Zhan, Qiangqiang Yuan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9416898/ |
Similar Items
-
Multi-Resolution Learning and Semantic Edge Enhancement for Super-Resolution Semantic Segmentation of Urban Scene Images
by: Ruijun Shu, et al.
Published: (2024-07-01) -
Building Extraction from Very-High-Resolution Remote Sensing Images Using Semi-Supervised Semantic Edge Detection
by: Liegang Xia, et al.
Published: (2021-06-01) -
A Comprehensive Survey of Tools and Software for Active Subnetwork Identification
by: Hung Nguyen, et al.
Published: (2019-03-01) -
Semantic Segmentation of Very-High-Resolution Remote Sensing Images via Deep Multi-Feature Learning
by: Yanzhou Su, et al.
Published: (2022-01-01) -
Precise Extraction of Buildings from High-Resolution Remote-Sensing Images Based on Semantic Edges and Segmentation
by: Liegang Xia, et al.
Published: (2021-08-01)