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<p class="MsoNormal"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">From:</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif"> Cosc-faculty [mailto:cosc-faculty-bounces@listserv.tamucc.edu]
<b>On Behalf Of </b>Carrasco, Margo<br>
<b>Sent:</b> Friday, April 13, 2018 12:32 PM<br>
<b>To:</b> COSC-faculty@listserv.tamucc.edu<br>
<b>Subject:</b> [Cosc-faculty] Thanh Pham _ Thesis 2 Defense<o:p></o:p></span></p>
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<p class="MsoNormal"><span style="color:black">Date: April 16 (Monday)<br>
Time: 2:00 pm <br>
Location: UC, Marlin Room 317<br>
Committee Members: <br>
Dr. Scott King<br>
Dr. Byung Cheol (Bruce) Lee<br>
Dr. Alaa Sheta</span><o:p></o:p></p>
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Thesis title: DETECTION OF PLANT CHARACTERISTICS AND A COMPARISON OF EFFECTIVENESS BETWEEN 2D AND 3D DATA VISUALIZATION IN SUPPORTING HUMAN PERCEPTION OF PLANT CHARACTERISTICS<br>
Abstract: Efficient agriculture requires the assessment of plant characteristics. The higher yield of crop can be achieved with good quality of plant characteristics data. In this research, a system was developed using the algorithms presented here to automatically
extract plant characteristics. The automatically extracted values were compared with ground-truth data to evaluate the accuracy of the system. As well, the effectiveness of using 2 or 3 dimensions when presenting plant data for determining these characteristics
is studied. An experiment was conducted to investigate how effective plant characteristics are evaluated when using 2D or 3D data visualizations. Participants were presented with either plant pictures (2D) or 3D plant models and tasked with identifying plant
height and number of leaves. Task completion times and accuracy rates were used for <o:p></o:p></p>
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