@Book{AntonioLopez2017,
author="Antonio Lopez
and Atsushi Imiya
and Tomas Pajdla
and Jose Manuel Alvarez",
title="Computer Vision in Vehicle Technology: Land, Sea \& Air",
year="2017",
publisher="John Wiley \& Sons, Ltd",
abstract="Summary This chapter examines different vision-based commercial solutions for real-live  problems related to vehicles. It is worth mentioning the recent astonishing performance of  deep convolutional neural networks (DCNNs) in difficult visual tasks such as image  classification, object recognition/localization/detection, and semantic segmentation. In fact, different DCNN architectures are already being explored for low-level tasks such as optical  flow and disparity computation, and higher level ones such as place recognition.",
optnote="ADAS; 600.118",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2937), last updated on Tue, 26 Apr 2022 20:24:15 +0200",
isbn="978-1-118-86807-2"
}