Deep Learning-Based Damage Detection from Aerial SfM Point Clouds

Deep Learning-Based Damage Detection from Aerial SfM Point Clouds

Aerial data collection is well known as an efficient method to study the impact following extreme events. While datasets predominately include images for post-disaster remote sensing analyses, images alone cannot provide detailed geometric information due to a lack of depth or the complexity require...

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Bibliographic Details
Main Authors: Mohammad Ebrahim Mohammadi, Daniel P. Watson, Richard L. Wood
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Drones
Subjects:
three-dimensional convolutional neural network
deep learning
unmanned aerial systems
semantic segmentation
point clouds
Hurricane Harvey
Online Access:https://www.mdpi.com/2504-446X/3/3/68

Internet

https://www.mdpi.com/2504-446X/3/3/68

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