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    <identifier>10.57760/sciencedb.05301</identifier>
    <datestamp>2022-11-27T23:05:13Z</datestamp>
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  <dc:date>2022-11-27</dc:date>
  <dc:title>Skeleton-Based Action Recognition Dataset Using Multi-Scale Spatial Temporal Graph Neural Network</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.05301</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>	The dataset file contains the experimental results of different methods. The table contains 6 columns. The first column indicates the GCN-based models, the 2nd column is models' parameter size, and the last 4 columns are the top-1 accuracies of the models.</dc:description>
  <dc:subject>Skeleton-based action recognition; spatial-temporal network; adaptive fusion</dc:subject>
  <dc:creator>Dong Feng</dc:creator>
  <dc:creator>ZhongCheng Wu</dc:creator>
  <dc:creator>Jun Zhang</dc:creator>
  <dc:creator>Tingting Ren</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1109/ACCESS.2021.3073107</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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