Building Damage Assessment Using Feature Concatenated Siamese Neural Network
Mgs M. Luthfi Ramadhan,
Grafika Jati,
Wisnu Jatmiko
Abstract:Fast and accurate post-earthquake building damage assessment is an important task to do to define search and rescue procedures. Many approaches have been proposed to automate this process by using artificial intelligence, some of which use handcrafted features that are considered inefficient. This research proposed end-to-end building damage assessment based on a Siamese neural network. We modify the network by adding a feature concatenation mechanism to enrich the data feature. This concatenation mechanism cr… Show more
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