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Computer Vision based inspection on post-earthquake with UAV synthetic dataset. (arXiv:2210.05282v1 [cs.CV])
Oct. 12, 2022, 1:11 a.m. | Mateusz Żarski, Bartosz Wójcik, Jarosław A. Miszczak, Bartłomiej Blachowski, Mariusz Ostrowski
cs.LG updates on arXiv.org arxiv.org
The area affected by the earthquake is vast and often difficult to entirely
cover, and the earthquake itself is a sudden event that causes multiple defects
simultaneously, that cannot be effectively traced using traditional, manual
methods. This article presents an innovative approach to the problem of
detecting damage after sudden events by using an interconnected set of deep
machine learning models organized in a single pipeline and allowing for easy
modification and swapping models seamlessly. Models in the pipeline were …
More from arxiv.org / cs.LG updates on arXiv.org
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