Learning to Extract Building Footprints From Off-Nadir Aerial Images
Author:
Affiliation:
1. School of Electronics, Wuhan University, Wuhan, China
2. University of Electronic Science and Technology of China, Chengdu, China
3. Sun Yat-Sen University, Guangzhou, China
4. School of Computer Science, Wuhan University, Wuhan, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/9970415/09743742.pdf?arnumber=9743742
Reference32 articles.
1. Boundary IoU: Improving Object-Centric Image Segmentation Evaluation
2. Feature Pyramid Networks for Object Detection
3. Deep Residual Learning for Image Recognition
4. DARNet: Deep Active Ray Network for Building Segmentation
5. MAP-Net: Multiple Attending Path Neural Network for Building Footprint Extraction From Remote Sensed Imagery
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