no code implementations • 19 Jan 2024 • André O. Françani, Marcos R. O. A. Maximo
Deep learning algorithms have driven expressive progress in many complex tasks.
1 code implementation • 20 Nov 2023 • Joao P. A. Dantas, Diego Geraldo, Felipe L. L. Medeiros, Marcos R. O. A. Maximo, Takashi Yoneyama
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems.
1 code implementation • 10 May 2023 • André O. Françani, Marcos R. O. A. Maximo
In this work, we deal with the monocular visual odometry as a video understanding task to estimate the 6-DoF camera's pose.
no code implementations • 19 Apr 2023 • Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama
This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment.
1 code implementation • 4 Oct 2022 • André O. Françani, Marcos R. O. A. Maximo
Monocular visual odometry consists of the estimation of the position of an agent through images of a single camera, and it is applied in autonomous vehicles, medical robots, and augmented reality.
1 code implementation • 9 Jul 2022 • Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air combat.
1 code implementation • 2 Mar 2022 • Rafael Figueiredo Prudencio, Marcos R. O. A. Maximo, Esther Luna Colombini
With the widespread adoption of deep learning, reinforcement learning (RL) has experienced a dramatic increase in popularity, scaling to previously intractable problems, such as playing complex games from pixel observations, sustaining conversations with humans, and controlling robotic agents.
1 code implementation • 3 Dec 2021 • Joao P. A. Dantas, Andre N. Costa, Marcos R. O. A. Maximo, Takashi Yoneyama
Besides, we employed hyperparameter tuning to identify the most critical features in the algorithm.
no code implementations • 4 Nov 2021 • Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range.
no code implementations • 4 Nov 2021 • Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work aims to provide an engagement decision support tool for Beyond Visual Range (BVR) air combat in the context of Defensive Counter Air (DCA) missions.
1 code implementation • 22 Oct 2019 • Luckeciano C. Melo, Marcos R. O. A. Maximo
In the current level of evolution of Soccer 3D, motion control is a key factor in team's performance.
1 code implementation • 22 Oct 2019 • Luckeciano C. Melo, Marcos R. O. A. Maximo, Adilson Marques da Cunha
Despite of the recent progress in agents that learn through interaction, there are several challenges in terms of sample efficiency and generalization across unseen behaviors during training.