93 citations · 276 across the 10 of their papers we have counts for
10 papers
Uniform Loss vs. Specialized Optimization: A Comparative Analysis in Multi-Task Learning
Gabriel S. Gama, Valdir Grassi
Specialized Multi-Task Optimizers (SMTOs) balance task learning in Multi-Task Learning by addressing issues like conflicting gradients and differing gradient norms, which hinder eq…
Autonomous driving of trucks in off-road environment
Kenny A. Q. Caldas, Filipe M. Barbosa, Junior A. R. Silva +5
Off-road driving operations can be a challenging environment for human conductors as they are subject to accidents, repetitive and tedious tasks, strong vibrations, which may affec…
Semantic SuperPoint: A Deep Semantic Descriptor
Gabriel S. Gama, Nícolas S. Rosa, Valdir Grassi
Several SLAM methods benefit from the use of semantic information. Most integrate photometric methods with high-level semantics such as object detection and semantic segmentation.…
Leveraging convergence behavior to balance conflicting tasks in multi-task learning
Angelica Tiemi Mizuno Nakamura, Denis Fernando Wolf, Valdir Grassi
Multi-Task Learning is a learning paradigm that uses correlated tasks to improve performance generalization. A common way to learn multiple tasks is through the hard parameter shar…
Robust path-following control design of heavy vehicles based on multiobjective evolutionary optimization
Gustavo Alves Prudencio de Morais, Lucas Barbosa Marcos, Filipe Marques Barbosa +3
The ability to deal with systems parametric uncertainties is an essential issue for heavy self-driving vehicles in unconfined environments. In this sense, robust controllers prove…
On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation
Raul de Queiroz Mendes, Eduardo Godinho Ribeiro, Nicolas dos Santos Rosa +1
Inferring the depth of images is a fundamental inverse problem within the field of Computer Vision since depth information is obtained through 2D images, which can be generated fro…