BDD-Net+: A Building Damage Detection Framework Based on Modified Coat-Net-Reference-Cited by-同舟云学术

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BDD-Net+: A Building Damage Detection Framework Based on Modified Coat-Net

Published:2023 Issue: Volume:16 Page:4232-4247
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Seydi Seyd Teymoor¹^ORCID,Hasanlou Mahdi¹^ORCID,Chanussot Jocelyn²^ORCID,Ghamisi Pedram³^ORCID

Affiliation:

1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2. CNRS, Grenoble INP, GIPSA-Lab, University Grenoble Alpes, Grenoble, France

3. Helmholtz-Zentrum Dresden-Rossendorf, Machine Learning Group, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/10103581.pdf?arnumber=10103581

Reference33 articles.

1. Earthquake Damage Region Detection by Multitemporal Coherence Map Analysis of Radar and Multispectral Imagery

2. A Novel Statistical Texture Feature for SAR Building Damage Assessment in Different Polarization Modes

3. A Multi-Feature Fusion Using Deep Transfer Learning for Earthquake Building Damage Detection

4. Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

5. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

Cited by 9 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. LiST-Net: Enhanced Flood Mapping With Lightweight SAR Transformer Network and Dimension-Wise Attention;IEEE Transactions on Geoscience and Remote Sensing;2024

2. EMYNet-BDD: EfficientViTB Meets Yolov8 in the Encoder–Decoder Architecture for Building Damage Detection Using Postevent Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Evaluation of Deep Learning Models for Building Damage Mapping in Emergency Response Settings;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. A Novel Weighted Ensemble Transferred U-Net Based Model (WETUM) for Postearthquake Building Damage Assessment From UAV Data: A Comparison of Deep Learning- and Machine Learning-Based Approaches;IEEE Transactions on Geoscience and Remote Sensing;2024

5. GES: A New Building Damage Data Augmentation and Detection Method Based on Extremely Imbalanced Data and Unique Spatial Distribution of Satellite Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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