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    <identifier>10.57760/sciencedb.31740</identifier>
    <datestamp>2025-11-20T12:23:19Z</datestamp>
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  <dc:date>2025-11-20</dc:date>
  <dc:title>RipAlert Dataset: Annotated Coastal Imagery for Early-Stage Rip Current Detection</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.31740</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset, curated for the RipAlert framework, comprises 1768 annotated frames for object detection. It is specifically curated to capture subtle, early-stage rip current patterns and support predictive modeling.The data was assembled by combining publicly available coastal footage with proprietary video collected via drone and shore surveillance in high-risk areas. Annotations include bounding boxes and confidence levels for rip current identification. This dataset is publicly released to promote reproducible research and advance AI applications for coastal safety.</dc:description>
  <dc:subject>Rip Current; Coastal Safety; Object Detection</dc:subject>
  <dc:creator>Liqiang Feng</dc:creator>
  <dc:creator>Meng Wan</dc:creator>
  <dc:creator>Jue Wang</dc:creator>
  <dc:creator>Rongqiang Cao</dc:creator>
  <dc:creator>Yangang Wang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-sa/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1609/aaai.v40i46.41286</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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