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Detecting surface defects of heritage buildings based on deep learning
X Fu, N Angkawisittpan - Journal of Intelligent Systems, 2024 - degruyter.com
The present study examined the usage of deep convolutional neural networks (DCNNs) for
the classification, segmentation, and detection of the images of surface defects in heritage …
the classification, segmentation, and detection of the images of surface defects in heritage …
[HTML][HTML] Trend classification of InSAR displacement time series using SAE–CNN
Multi-temporal Interferometric Synthetic Aperture Radar technique (MTInSAR) has emerged
as a valuable tool for measuring ground motion in a wide area. However, interpreting …
as a valuable tool for measuring ground motion in a wide area. However, interpreting …
Automatic Detection of Building Displacements Through Unsupervised Learning From InSAR Data
We introduce an unsupervised learning method that aims to identify building anomalies
using Interferometric Synthetic Aperture Radar (InSAR) time-series data. Specifically, we …
using Interferometric Synthetic Aperture Radar (InSAR) time-series data. Specifically, we …