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<title>MegaPixels</title>
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<div class='site_name'>MegaPixels</div>
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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Unconstrained College Students (UCCS)</span> is a dataset of images ...</span></div><div class='hero_subdesc'><span class='bgpad'>The UCCS dataset includes ...
</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>Unconstrained College Students ...</h2>
<p>(PAGE UNDER DEVELOPMENT)</p>
</section><section>
<h3>Information Supply Chain</h3>
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<li><span style="color: #f2f293">■</span> Industry</li>
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<li><span style="color: #3264f6">■</span> Government</li>
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<p>
To understand how UCCS has been used around the world...
affected global research on computer vision, surveillance, defense, and consumer technology, the and where this dataset has been used the locations of each organization that used or referenced the datast
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<div class="map-legend-item edu">Academic</div>
<div class="map-legend-item com">Industry</div>
<div class="map-legend-item gov">Government</div>
Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a> and not yet manually verified.
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<h2>Supplementary Information</h2>
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<h3>Citations</h3>
<p>
Citations were collected from <a href="https://www.semanticscholar.org">Semantic Scholar</a>, a website which aggregates
and indexes research papers. Metadata was extracted from these papers, including extracting names of institutions automatically from PDFs, and then the addresses were geocoded. Data is not yet manually verified, and reflects anytime the paper was cited. Some papers may only mention the dataset in passing, while others use it as part of their research methodology.
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</section><section><h3>Research Notes</h3>
<p>The original Sapkota and Boult dataset, from which UCCS is derived, received funding from<sup class="footnote-ref" id="fnref-funding_sb"><a href="#fn-funding_sb">1</a></sup>:</p>
<ul>
<li>ONR (Office of Naval Research) MURI (The Department of Defense Multidisciplinary University Research Initiative) grant N00014-08-1-0638</li>
<li>Army SBIR (Small Business Innovation Research) grant W15P7T-12-C-A210</li>
<li>SOCOM (Special Operations Command) SBIR (Small Business Innovation Research) grant H92222-07-P-0020</li>
</ul>
<p>The more recent UCCS version of the dataset received funding from <sup class="footnote-ref" id="fnref-funding_uccs"><a href="#fn-funding_uccs">2</a></sup>:</p>
<ul>
<li>National Science Foundation Grant IIS-1320956</li>
<li>ODNI (Office of Director of National Intelligence)</li>
<li>IARPA (Intelligence Advance Research Projects Activity) R&D contract 2014-14071600012</li>
</ul>
<div class="footnotes">
<hr>
<ol><li id="fn-funding_sb"><p>Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.<a href="#fnref-funding_sb" class="footnote">↩</a></p></li>
<li id="fn-funding_uccs"><p>Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.<a href="#fnref-funding_uccs" class="footnote">↩</a></p></li>
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