Zobrazeno 1 - 10
of 2 352
pro vyhledávání: '"Pinto João"'
Autor:
Gomes Ruan G.S., Gomes Guilherme J.C., Vargas Eurípedes A., van Genuchten Martinus Th., Pinto João T.M.G., Rosa Felipe A.
Publikováno v:
Journal of Hydrology and Hydromechanics, Vol 70, Iss 2, Pp 244-256 (2022)
Field tests were carried out to estimate effective unsaturated soil hydraulic properties of layered residual soils in Rio de Janeiro, southeastern Brazil. Data of this type are important for understanding the initiation of rainstorm-induced soil land
Externí odkaz:
https://doaj.org/article/34bb5b7c8e6c491c8baae082af5e6e73
Autor:
Sousa-Pinto, João, Orban, Dominique
We present a new algorithm for solving linear-quadratic regulator (LQR) problems with linear equality constraints, also known as constrained LQR (CLQR) problems. Our method's sequential runtime is linear in the number of stages and constraints, and i
Externí odkaz:
http://arxiv.org/abs/2407.05433
Autor:
Serrano, Gil, Jacinto, Marcelo, Ribeiro-Gomes, Jose, Pinto, Joao, Guerreiro, Bruno J., Bernardino, Alexandre, Cunha, Rita
Recent advances in aerial robotics have enabled the use of multirotor vehicles for autonomous payload transportation. Resorting only to classical methods to reliably model a quadrotor carrying a cable-slung load poses significant challenges. On the o
Externí odkaz:
http://arxiv.org/abs/2405.09428
Autor:
Sousa-Pinto, João, Orban, Dominique
We introduce a new algorithm for solving unconstrained discrete-time optimal control problems. Our method follows a direct multiple shooting approach, and consists of applying the SQP method together with an $\ell_2$ augmented Lagrangian primal-dual
Externí odkaz:
http://arxiv.org/abs/2403.00748
Autor:
Jacinto, Marcelo, Pinto, João, Patrikar, Jay, Keller, John, Cunha, Rita, Scherer, Sebastian, Pascoal, António
Developing and testing novel control and motion planning algorithms for aerial vehicles can be a challenging task, with the robotics community relying more than ever on 3D simulation technologies to evaluate the performance of new algorithms in a var
Externí odkaz:
http://arxiv.org/abs/2307.05263
Autor:
Pinto, João Ribeiro
Artificially intelligent perception is increasingly present in the lives of every one of us. Vehicles are no exception, (...) In the near future, pattern recognition will have an even stronger role in vehicles, as self-driving cars will require autom
Externí odkaz:
http://arxiv.org/abs/2301.03045
Autor:
Falcão Carneiro, João1,2 (AUTHOR) fga@fe.up.pt, Bravo Pinto, João2 (AUTHOR) nacruz@fe.up.pt, Gomes de Almeida, Fernando1,2 (AUTHOR), Cruz, Nuno A.2,3 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2024, Vol. 24 Issue 17, p5771. 19p.
Autor:
Neto, Pedro C., Gonçalves, Tiago, Pinto, João Ribeiro, Silva, Wilson, Sequeira, Ana F., Ross, Arun, Cardoso, Jaime S.
As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals. However, the latter can only be complete when seen through the lens of the causality framework. As such
Externí odkaz:
http://arxiv.org/abs/2208.09500
Autor:
Neto, Pedro C., Boutros, Fadi, Pinto, Joao Ribeiro, Damer, Naser, Sequeira, Ana F., Cardoso, Jaime S., Bengherabi, Messaoud, Bousnat, Abderaouf, Boucheta, Sana, Hebbadj, Nesrine, Erakın, Mustafa Ekrem, Demir, Uğur, Ekenel, Hazım Kemal, Vidal, Pedro Beber de Queiroz, Menotti, David
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 attracted a total of 3 participating teams, from academia. Eventually,
Externí odkaz:
http://arxiv.org/abs/2208.02760