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Luís P. N. Mendes, Ana M. C. Ricardo, Alexandre J. M. Bernardino and Rui M. L. Ferreira
We present novel velocimetry algorithms based on the hybridization of correlation-based Particle Image Velocimetry (PIV) and a combination of Lucas?Kanade and Liu?Shen optical flow (OpF) methods. An efficient Aparapi/OpenCL implementation of those method...
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José-Luis Molina, Santiago Zazo, Fernando Espejo, Carmen Patino-Alonso, Irene Blanco-Gutiérrez and Domingo Zarzo
Floods are probably the most hazardous global natural event as well as the main cause of human losses and economic damage. They are often hard to predict, but their consequences may be reduced by taking the right precautions. In this sense, hydraulic inf...
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Andrea D?Ambrosio and Roberto Furfaro
This paper demonstrates the utilization of Pontryagin Neural Networks (PoNNs) to acquire control strategies for achieving fuel-optimal trajectories. PoNNs, a subtype of Physics-Informed Neural Networks (PINNs), are tailored for solving optimal control pr...
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Junlin Lou, Burak Yuksek, Gokhan Inalhan and Antonios Tsourdos
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and trajectory that cost minimal time to reach a goal location in the presence of dynamic geo-fences and uncertainties in ...
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Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
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