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        <datestamp>2026-09-16T08:21:55Z</datestamp>
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          <dc:title>&lt;b&gt;Dataset and Source Code for Diagnosing Cultural Bias in AVA Trained Aesthetic Scoring&lt;/b&gt;</dc:title>
          <dc:creator>Nargiz Aghayeva (24964348)</dc:creator>
          <dc:subject>Artificial intelligence not elsewhere classified</dc:subject>
          <dc:subject>Computer vision</dc:subject>
          <dc:subject>Image processing</dc:subject>
          <dc:subject>Machine learning not elsewhere classified</dc:subject>
          <dc:subject>aesthetic assessment</dc:subject>
          <dc:subject>aesthetic scoring</dc:subject>
          <dc:subject>computer vision</dc:subject>
          <dc:subject>deep learning</dc:subject>
          <dc:subject>cultural bias</dc:subject>
          <dc:subject>cultural distribution shift</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:subject>image aesthetics</dc:subject>
          <dc:subject>NIMA</dc:subject>
          <dc:subject>ResNet18</dc:subject>
          <dc:subject>Grad-CAM</dc:subject>
          <dc:subject>Wikimedia Commons</dc:subject>
          <dc:subject>dataset</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This repository contains the dataset, source code, and supporting materials used in the study “Diagnosing Cultural Bias in AVA Trained Aesthetic Scoring: A Ground Truth Free Framework.”&lt;/p&gt;&lt;p dir="ltr"&gt;The repository provides the materials required to reproduce the data analysis and experimental procedures described in the associated research study. It includes the evaluation datasets, source code, analysis scripts, model related files, and supporting documentation.&lt;/p&gt;&lt;p dir="ltr"&gt;The repository is intended to provide transparent access to the computational materials used in the study and to facilitate reproducibility and further research on cultural distribution shift in aesthetic assessment models.&lt;/p&gt;&lt;p dir="ltr"&gt;The evaluation images were sourced from Wikimedia Commons and are subject to their respective original licenses. The &lt;code&gt;provenance.csv&lt;/code&gt; file provides the Wikimedia source URL, original license, and artist information for each image included in the released dataset. Users are responsible for complying with the applicable license and attribution requirements for each individual image.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-16T08:21:55Z</dc:date>
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          <dc:identifier>10.6084/m9.figshare.33832042.v1</dc:identifier>
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