1 code implementation • 4 Jun 2019 • Lucas C. Possatti, Rânik Guidolini, Vinicius B. Cardoso, Rodrigo F. Berriel, Thiago M. Paixão, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
However, none of them combine the power of the deep learning-based detectors with prior maps to recognize the state of the relevant traffic lights.
no code implementations • 27 Apr 2018 • Raphael V. Carneiro, Rafael C. Nascimento, Rânik Guidolini, Vinicius B. Cardoso, Thiago Oliveira-Santos, Claudine Badue, Alberto F. de Souza
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 signalization, in order to allow the operation of autonomous cars in such situations.
no code implementations • 4 Oct 2018 • Thomas Teixeira, Filipe Mutz, Karin Satie Komati, Lucas Veronese, Vinicius B. Cardoso, Claudine Badue, Thiago Oliveira-Santos, Alberto F. de Souza
The objective of map decay is to correct invalid occupancy probabilities of map cells that are unobservable by sensors.
no code implementations • 2 Oct 2019 • Pedro Azevedo, Sabrina S. Panceri, Rânik Guidolini, Vinicius B. Cardoso, Claudine Badue, Thiago Oliveira-Santos, Alberto F. de Souza
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.