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Zhixin Li, Song Ji, Dazhao Fan, Zhen Yan, Fengyi Wang and Ren Wang
Accurate building geometry information is crucial for urban planning in constrained spaces, fueling the growing demand for large-scale, high-precision 3D city modeling. Traditional methods like oblique photogrammetry and LiDAR prove time consuming and ex...
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Jian Liu, Shihui Yu, Xuemei Liu, Guohang Lu, Zhenbo Xin and Jin Yuan
In-field in situ droplet deposition digitization is beneficial for obtaining feedback on spraying performance and precise spray control, the cost-effectiveness of the measurement system is crucial to its scalable application. However, the limitations of ...
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P. C. Iglesias, L. Godinho and J. Redondo
Extracting the microscopic parameters of a porous material is a complex task, and attempts have been made to develop models that can simulate their characteristics, gathering the least amount of information possible. As a case in point, tests to evaluate...
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Benjamin Burrichter, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach
This study employs a temporal fusion transformer (TFT) for predicting overflow from sewer manholes during heavy rainfall events. The TFT utilised is capable of forecasting overflow hydrographs at the manhole level and was tested on a sewer network with 9...
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Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl...
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