1 citations · 1 across the 1 of their papers we have counts for
6 papers
Bio-Inspired Foveated Technique for Augmented-Range Vehicle Detection Using Deep Neural Networks
Pedro Azevedo, Sabrina S. Panceri, Rânik Guidolini +4
We propose a bio-inspired foveated technique to detect cars in a long range camera view using a deep convolutional neural network (DCNN) for the IARA self-driving car. The DCNN rec…
Traffic Light Recognition Using Deep Learning and Prior Maps for Autonomous Cars
Lucas C. Possatti, Rânik Guidolini, Vinicius B. Cardoso +5
Autonomous terrestrial vehicles must be capable of perceiving traffic lights and recognizing their current states to share the streets with human drivers. Most of the time, human d…
Self-Driving Cars: A Survey
Claudine Badue, Rânik Guidolini, Raphael Vivacqua Carneiro +10
We survey research on self-driving cars published in the literature focusing on autonomous cars developed since the DARPA challenges, which are equipped with an autonomy system tha…
Memory-like Map Decay for Autonomous Vehicles based on Grid Maps
Thomas Teixeira, Filipe Mutz, Karin Satie Komati +5
In this work, we present a novel strategy for correcting imperfections in occupancy grid maps called map decay. The objective of map decay is to correct invalid occupancy probabili…
Mapping Road Lanes Using Laser Remission and Deep Neural Networks
Raphael V. Carneiro, Rafael C. Nascimento, Rânik Guidolini +4
We propose the use of deep neural networks (DNN) for solving the problem of inferring the position and relevant properties of lanes of urban roads with poor or absent horizontal si…
A Model-Predictive Motion Planner for the IARA Autonomous Car
Vinicius Cardoso, Josias Oliveira, Thomas Teixeira +5
We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a…