Building Footprint Extraction Using Deep Learning Semantic Segmentation Techniques: Experiments and Results-Reference-Cited by-同舟云学术

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Building Footprint Extraction Using Deep Learning Semantic Segmentation Techniques: Experiments and Results

Published:2021-07-11 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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Author:

Borba Philipe,de Carvalho Diniz Felipe,da Silva Nilton Correia,de Souza Bias Edilson

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9553015/9553016/09553855.pdf?arnumber=9553855

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extraction of building from remote sensing imagery base on multi-attention L-CAFSFM and MFFM;Frontiers in Earth Science;2023-10-19

2. On the Robustness and Generalization Ability of Building Footprint Extraction on the Example of SegNet and Mask R-CNN;Remote Sensing;2023-04-18

3. Comparison of Semantic Segmentation Deep Learning Methods for Building Extraction;2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM);2022-11-22

4. Comparing the robustness of U-Net, LinkNet, and FPN towards label noise for refugee dwelling extraction from satellite imagery;2022 IEEE Global Humanitarian Technology Conference (GHTC);2022-09-08

5. Assessing the Influences of Band Selection and Pretrained Weights on Semantic-Segmentation-Based Refugee Dwelling Extraction from Satellite Imagery;AGILE: GIScience Series;2022-06-10

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