25 citations · 26 across the 9 of their papers we have counts for
3 papers · 1 filter
A Performance Increment Strategy for Semantic Segmentation of Low-Resolution Images from Damaged Roads
Rafael S. Toledo, Cristiano S. Oliveira, Vitor H. T. Oliveira +2
Autonomous driving needs good roads, but 85% of Brazilian roads have damages that deep learning models may not regard as most semantic segmentation datasets for autonomous driving…
Physics-Informed Echo State Networks for Modeling Controllable Dynamical Systems
Eric Mochiutti, Eric Aislan Antonelo, Eduardo Camponogara
Echo State Networks (ESNs) are recurrent neural networks usually employed for modeling nonlinear dynamic systems with relatively ease of training. By incorporating physical laws in…
Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells
Jonas Ekeland Kittelsen, Eric Aislan Antonelo, Eduardo Camponogara +1
Neural networks, while powerful, often lack interpretability. Physics-Informed Neural Networks (PINNs) address this limitation by incorporating physics laws into the loss function,…