@article{ref1,
title="Multi-column deep neural network for traffic sign classification",
journal="Neural networks",
year="2012",
author="Cireşan, Dan and Meier, Ueli and Masci, Jonathan and Schmidhuber, Jürgen",
volume="32",
number="",
pages="333-338",
abstract="We describe the approach that won the final phase of the German traffic sign recognition benchmark. Our method is the only one that achieved a better-than-human recognition rate of 99.46%. We use a fast, fully parameterizable GPU implementation of a Deep Neural Network (DNN) that does not require careful design of pre-wired feature extractors, which are rather learned in a supervised way. Combining various DNNs trained on differently preprocessed data into a Multi-Column DNN (MCDNN) further boosts recognition performance, making the system insensitive also to variations in contrast and illumination.<p /> <p>Language: en</p>",
language="en",
issn="0893-6080",
doi="10.1016/j.neunet.2012.02.023",
url="http://dx.doi.org/10.1016/j.neunet.2012.02.023"
}