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Xia, Yitong (author)
The reconstruction of 3D city models has garnered significant interest in recent years. However, the majority of existing reconstruction methods primarily focus on LOD2 models, while LOD3 model reconstruction often relies on manual labor, and the primary data sources are street view images. This research aims to advance this field by...
master thesis 2023
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Cui, Jianfeng (author)
We explored the possibility of improving cross-view matching performance with self-supervised learning techniques and perform interpretations in terms of the embedding space of image features. The effect of pre-training by contrastive learning is verified quantitatively by experiments, and also exhibited by visualization of the feature space.
master thesis 2023
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Bai, Qian (author)
Roads in modern cities facilitate different types of users, including car drivers, cyclists, and pedestrians. These different users often have a designated section of the road to operate on. Road management, e.g., by municipalities, needs to take this sectioning into account, preferably in an efficient way. Mobile laser scanning (MLS) point...
master thesis 2021
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Prins, Hessel (author)
An increasing load on the Dutch rail network requires new solutions for railway monitoring as increasing wear and tighter schedules limit the possibilities of regular maintenance. UAV (Unmanned Aerial Vehicle) based photogrammetry is such a solution which limits the presence of people near the railway and train hindrance. Photogrammetric feature...
master thesis 2021
document
Bai, Qian (author)
Semantic segmentation of aerial point clouds with high accuracy is significant for many geographical applications, but is not trivial since the data is massive and unstructured. In the past few years, deep learning approaches designed for 3D point cloud data have made great progress. Pointwise neural networks, such as PointNet and its extensions...
student report 2020
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