Reliability Estimation for Neural Network Based Autonomous Driving
Journal Article, Robotics and Autonomous Systems, Vol. 12, No. 4, pp. 113 - 119, April, 1994
Abstract
This paper describes a technique called Input Reconstruction Reliability Estimation (IRRE) for determining the response reliability of a restricted class of multi-layer perceptrons (MLPs). The technique uses a network's ability to accurately encode the input pattern in its internal representation as a measure of its reliability. The more accurately a network is able to reconstruct the input pattern from its internal representation, the more reliable the network is considered to be. IRRE provides a good estimate of the reliability of MLPs trained for autonomous driving. Results are presented in which the reliability estimates provided by IRRE are used to select between networks trained for different driving situations.
BibTeX
@article{Pomerleau-1994-16049,author = {Dean Pomerleau},
title = {Reliability Estimation for Neural Network Based Autonomous Driving},
journal = {Robotics and Autonomous Systems},
year = {1994},
month = {April},
volume = {12},
number = {4},
pages = {113 - 119},
}
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