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    <identifier>10.57760/sciencedb.23965</identifier>
    <datestamp>2025-04-23T09:01:01Z</datestamp>
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  <dc:date>2025-04-23</dc:date>
  <dc:title>Multi-model Deep learning of Traditional Architectures</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.23965</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset and code are used to for analyzing the tourist engagement with traditional architectures through BERT and ViT-Large model. A case study of Xi'an Gao Family Compound was carried out in this research. The data includes:Image dataset for training the ViT model.Python Code and Log files of the training process.The trained ViT-model in .pth format and training report.Due to the protection of personal information, the images for the classification is not shared here.Python Code and Log files of the classification process.Log files and classification resultsFiltered text for Bert-analysisPython Code and Bert-analysis results </dc:description>
  <dc:subject>BERT; ViT; traditional Chinese architecture; deep learning; social media</dc:subject>
  <dc:creator>Liyue Wu</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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