Geometric Boundary Guided Feature Fusion and Spatial-Semantic Context Aggregation for Semantic Segmentation of Remote Sensing Images
Author:
Affiliation:
1. Beijing Institute of Technology, Beijing, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/9991910/10298027.pdf?arnumber=10298027
Reference60 articles.
1. Land-cover classification with high-resolution remote sensing images using transferable deep models;tong;arXiv 1807 05713,2018
2. BSNet: Dynamic Hybrid Gradient Convolution Based Boundary-Sensitive Network for Remote Sensing Image Segmentation
3. Maritime Semantic Labeling of Optical Remote Sensing Images with Multi-Scale Fully Convolutional Network
4. Dual Attention Feature Fusion and Adaptive Context for Accurate Segmentation of Very High-Resolution Remote Sensing Images
5. Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
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