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    <title>Region Proposals on ViCoS Lab</title>
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      <title>Domain-specific adaptations for region proposals</title>
      <link>/publications/tabernik2015domain-specific/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;In this work we propose a novel approach towards the detection of all traffic sign boards. We propose to employ state-of-the-art region proposals as the first step to reduce the initial search space and provide a way to use a strong classifier for a fine-grade classification. We evaluate multiple region proposals on the domain of traffic sign detection and further propose various domain-specific adaptations to improve their performance. We show that edgeboxes with domain-specific learning and re-scoring based on trained shape information are able to significantly outperform remaining methods on German Traffic Sign Database. Furthermore, we show they achieve higher rate of recall with high-quality regions at the lower number of regions than the remaining methods.&lt;/p&gt;</description>
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      <title>Quality of region proposals in traffic sign detection and recognition</title>
      <link>/publications/tabernik2015quality/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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