Deep learning has achieved state-of-the-art performance on several compu...
Deep learning has achieved state-of-the-art performance on several compu...
The analysis of Magnetic Resonance Imaging (MRI) sequences enables clini...
Convolutional neural networks have been successful lately enabling compa...
Deep neural networks come as an effective solution to many problems
asso...
The localization of self-driving cars is needed for several tasks such a...
Deep learning has been successfully applied to several problems related ...
The reconstruction of shredded documents consists of coherently arrangin...
One of the main factors that contributed to the large advances in autono...
The reconstruction of shredded documents consists in arranging the piece...
We propose a bio-inspired foveated technique to detect cars in a long ra...
Deep learning has been successfully applied to several problems related ...
Deep learning techniques have enabled the emergence of state-of-the-art
...
Autonomous terrestrial vehicles must be capable of perceiving traffic li...
Multi-Domain Learning (MDL) refers to the problem of learning a set of m...
We survey research on self-driving cars published in the literature focu...
In this work, we present a novel strategy for correcting imperfections i...
Decreasing costs of vision sensors and advances in embedded hardware boo...
In the past few years, Convolutional Neural Networks (CNNs) have been
ac...
Correctly identifying crosswalks is an essential task for the driving
ac...
Currently, self-driving cars rely greatly on the Global Positioning Syst...
We propose the use of deep neural networks (DNN) for solving the problem...
High-resolution satellite imagery have been increasingly used on remote
...