no code implementations • 26 Mar 2021 • Javier Del Ser, David Casillas-Perez, Laura Cornejo-Bueno, Luis Prieto-Godino, Julia Sanz-Justo, Carlos Casanova-Mateo, Sancho Salcedo-Sanz
In this paper we review the most important characteristics of randomization-based machine learning approaches and their application to renewable energy prediction problems.
no code implementations • 14 Jul 2020 • David Fuentes-Jimenez, Cristina Losada-Gutierrez, David Casillas-Perez, Javier Macias-Guarasa, Roberto Martin-Lopez, Daniel Pizarro, Carlos A. Luna
This paper proposes a DNN-based system that detects multiple people from a single depth image.
no code implementations • 13 Jun 2020 • Adrian Sanchez-Caballero, Sergio de López-Diz, David Fuentes-Jimenez, Cristina Losada-Gutiérrez, Marta Marrón-Romera, David Casillas-Perez, Mohammad Ibrahim Sarker
Human actions recognition is a fundamental task in artificial vision, that has earned a great importance in recent years due to its multiple applications in different areas.
2 code implementations • 1 Jun 2020 • David Fuentes-Jimenez, Roberto Martin-Lopez, Cristina Losada-Gutierrez, David Casillas-Perez, Javier Macias-Guarasa, Daniel Pizarro, Carlos A. Luna
In this paper we propose a method based on deep learning that detects multiple people from a single overhead depth image with high reliability.
no code implementations • 19 Nov 2018 • David Fuentes-Jimenez, David Casillas-Perez, Daniel Pizarro, Toby Collins, Adrien Bartoli
Compared to previous non-DNN SfT methods, it does not involve numerical optimization at run-time, and is a dense, wide-baseline solution that does not demand, and does not suffer from, feature-based matching.
no code implementations • 11 Oct 2017 • David Casillas-Perez, Daniel Pizarro, Manuel Mazo, Adrien Bartoli
It is an important problem as it does not need initial conditions to obtain the unique solution and its the frequent solution that practical algorithms of the state-of-the-art give.