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    <identifier>10.57760/sciencedb.j00240.00036</identifier>
    <datestamp>2025-04-07T08:25:31Z</datestamp>
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  <dc:date>2025-04-07</dc:date>
  <dc:title>MVRSD_dataset</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00240.00036</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The dataset is derived from Google Earth data, collected 3,000 remotely sensed&amp;nbsp;images from more than 40 military scenarios within Asia, North America and Europe, and 32,626 military vehicle targets&amp;nbsp;were acquired from the remotely sensed images. The spatial resolution of the image is 0.3m and the size is 640&amp;times; 640. The&amp;nbsp;dataset consists of remotely sensed images and corresponding labeled files, and the targets were manually selected and&amp;nbsp;classified by experts through the interpretation of high-resolution optical images. The granular categories in the dataset are&amp;nbsp;divided into five categories based on vehicle size and military function: Small Military Vehicles (SMV), Large Military&amp;nbsp;Vehicles (LMV), Armored Fighting Vehicles (AFV), Military Construction Vehicles (MCV), and Civilian Vehicles (CV).&amp;nbsp;Military Construction Vehicles (MCV), Civilian Vehicles (CV). The geographic environments of the samples include cities,&amp;nbsp;plains, mountains and deserts.&amp;nbsp;</dc:description>
  <dc:subject>target detection; military vehicle dataset; high-resolution remote sensing; fine-grained; deep learning</dc:subject>
  <dc:creator>bai dong</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.11834/jig.230884</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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