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<!DOCTYPE HTML>
<head>
<title>iDVL News</title>
<link rel="shortcut icon" href="images/iDVLlogo/V2.png">
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<div class="content newsBox">
<h4><headline>IDVL Team win VAST Challenge Honorable Mention</headline></h4><h5><date>Aug
15,
2020</date></h5><p><fullNews>
<div class="news">
<center><h2>IDVL Team won VAST Mini-Challenge 2 Honorable Mention:<br> Detailed
Analysis of
Patterns of Misclassification</h2></center>
<p/>
The <a href="https://vast-challenge.github.io/2020/index.html"> VAST Challenge </a>
is an annual contest with the goal of advancing the field of visual analytics through competition. This
year, the VAST Challenge asks participants to apply visual analytics to solve three mini-challenges to
help a world impacted by a worldwide cyber event.
<p/>
<p>The IDVL Team consists of four Ph.D. students in Computer Science: <a target="_blank"
href="https://huyen-nguyen.github.io/">Huyen N. Nguyen</a>,
<a target="_blank" href="https://www.linkedin.com/in/jake-gonzalez-551306b4/">Jake Gonzalez</a>, <a
target="_blank" href="https://www.linkedin.com/in/jianguo-profile/">Jian Guo</a>, and <a
target="_blank" href="http://www.myweb.ttu.edu/ngu00336/">Ngan V.T. Nguyen</a>.
The team participated in Mini-Challenge 2: Object of the Search, which focused on a process for
using visual analytics to correct for classification errors in the results provided by a machine
learning
model. The ultimate goal of this challenge is to use patterns of misclassification analysis to
identify a group of people having a special item - a totem.</p>
<p>
The team has built an interactive visual analytics pipeline that included methods for visually analyzing
photographic image data as well as performing visual analytics on the statistical data, with
responsive visualization.
</p>
<p>
The report for the challenge can be found <a target="_blank"
href="https://huyen-nguyen.github.io/VAST2020mc2/TTU-Nguyen-MC2/">here</a>; the video and demonstration
can be found <a target="_blank"
href="https://huyen-nguyen.github.io/VAST2020mc2/">here</a>.
<br><br>
<embed src="https://www.youtube.com/embed/qD7VIXxFR5s" width="100%" height="456px" allowfullscreen="true"/>
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