Monitoring bridge health using vibrations of drive-by vehicles has various benefits, such as no need for directly installing and maintaining sensors on the bridge.
The supervised learning requires historical structural response data and corresponding damage states (i. e., labels) for each building to learn the building-specific damage diagnosis model.
1 code implementation • 28 Aug 2019 • Asim Smailagic, Pedro Costa, Alex Gaudio, Kartik Khandelwal, Mostafa Mirshekari, Jonathon Fagert, Devesh Walawalkar, Susu Xu, Adrian Galdran, Pei Zhang, Aurélio Campilho, Hae Young Noh
Our online method enhances performance of its underlying baseline deep network.
In this work, we give new results on the benefits of multi-generator architecture of GANs.
Active learning techniques can be used to minimize the number of required training labels while maximizing the model's performance. In this work, we propose a novel sampling method that queries the unlabeled examples that maximize the average distance to all training set examples in a learned feature space.