DeepLabV3_FP : a novel deep learning network for hurricane damage assessment of buildings in UAV imagery-Reference-Cited by-同舟云学术

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DeepLabV3_FP : a novel deep learning network for hurricane damage assessment of buildings in UAV imagery

Published:2023-10-28 Issue: Volume:14 Page:1-6
ISSN:
Container-title:2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
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Author:

Han Dongzhe¹,Yang Guang¹,Lu Wangze¹,Xie Runbo¹

Affiliation:

1. Institute Of Disaster Prevention,Software Engineering Technology Research Center,Sanhe,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10373215/10373216/10373267.pdf?arnumber=10373267

Reference16 articles.

1. Hurricane Building Damage Assessment using Post-Disaster UAV Data

2. Automated Poststorm Damage Classification of Low-Rise Building Roofing Systems Using High-Resolution Aerial Imagery

3. Texture Aware Unsupervised Segmentation for Assessment of Flood Severity in UAV Aerial Images

4. Transfer Learning-Based Automatic Hurricane Damage Detection Using Satellite Images

5. Using Artificial Neural Network Models to Assess Hurricane Damage through Transfer Learning

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