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    <identifier>10.57760/sciencedb.20383</identifier>
    <datestamp>2025-04-21T16:20:25Z</datestamp>
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  <dc:date>2025-04-21</dc:date>
  <dc:title>PaveTrack: A Large-Scale Image Repository for Automated Pavement Distress Analysis and Degradation Trend Prediction</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.20383</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The dataset in this study consists of two components: the first component is the annotation of pavement distress, wherein all identified instances of distress are annotated by enclosing them with bounding boxes and classified by appending the appropriate category labels. The second component involves long-term photographic tracking of certain pavement distresses, accompanied by refined segmentation to evaluate changes in the morphology and area of the distresses.</dc:description>
  <dc:subject>pavement distress detection; large-scale measurement; Pavement Deterioration Tracking</dc:subject>
  <dc:creator>Hanlin Yang</dc:creator>
  <dc:creator>Jinpu Cao</dc:creator>
  <dc:creator>Jun Wan</dc:creator>
  <dc:creator>Qian Gao</dc:creator>
  <dc:creator>Chenglong Liu</dc:creator>
  <dc:creator>Martin Fischer</dc:creator>
  <dc:creator>Yuchuan Du</dc:creator>
  <dc:creator>Yishun Li</dc:creator>
  <dc:creator>Pooja Jain</dc:creator>
  <dc:creator>Difei Wu</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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