<?xml version='1.0' encoding='utf-8'?>
<documents xmlns='http://eprints.org/ep2/data/2.0'>
  <document id='https://researchdata.bath.ac.uk/id/document/19176'>
    <docid>19176</docid>
    <rev_number>4</rev_number>
    <files>
      <file id='https://researchdata.bath.ac.uk/id/file/76668'>
        <fileid>76668</fileid>
        <datasetid>document</datasetid>
        <objectid>19176</objectid>
        <filename>train_CNN_stress.py</filename>
        <mime_type>text/x-script.python</mime_type>
        <hash>c26f62202ebdccbd904d3660150b4345</hash>
        <hash_type>MD5</hash_type>
        <filesize>19638</filesize>
        <mtime>2025-06-07 12:13:48</mtime>
        <url>https://researchdata.bath.ac.uk/1532/8/train_CNN_stress.py</url>
      </file>
    </files>
    <eprintid>1532</eprintid>
    <pos>8</pos>
    <placement>8</placement>
    <mime_type>text/x-script.python</mime_type>
    <format>other</format>
    <formatdesc>A Python script that can be used to train and evaluate a CNN for stress prediction.</formatdesc>
    <language>en</language>
    <security>public</security>
    <license>cc_mit</license>
    <main>train_CNN_stress.py</main>
    <content>code</content>
  </document>
</documents>
