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<dc:title xml:lang="pl"><![CDATA[Vision-based positioning of electric buses for assisted docking to charging stations]]></dc:title>
<dc:creator><![CDATA[Nowak, Tomasz]]></dc:creator>
<dc:creator><![CDATA[Nowicki, Michał]]></dc:creator>
<dc:creator><![CDATA[Skrzypczyński, Piotr]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[AI transport]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[localization]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[monocular vision]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[deep learning]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[keypoints]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[advanced driver assistance system]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[We present a novel approach to vision-based localization of electric city buses for assisted docking to a charging station. The method assumes that the charging station is a known object, and employs a monocular camera system for positioning upon carefully selected point features detected on the charging station. While the pose is estimated using a geometric method and taking advantage of the known structure of the feature points, the detection of keypoints themselves and the initial recognition of the charging station are accomplished using neural network models.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[We propose two novel neural network architectures for the estimation of keypoints. Extensive experiments presented in the paper made it possible to select the MRHKN architecture as the one that outperforms state-of-the-art keypoint detectors in the task considered, and offers the best performance with respect to the estimated translation and rotation of the bus with a low-cost hardware setup and minimal passive markers on the charging station.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Yao, Baozhen - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Wang, Shuaian - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Asian, Sobhan - ed.]]></dc:contributor>
<dc:date><![CDATA[2022]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/86509/AMCS_2022_32_4_5.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/101534/edition/86509/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:86509]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 32, number 4 (2022)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=126]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:101534]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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