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<span style="font-size:18.0pt;line-height:106%;font-family:"Arial",sans-serif">Félicitations aux étudiants
<b>Wougens Vincent</b> (mathématiques) et <b>Amos Noël</b> (génie informatique), ainsi qu’au professeur
<b>Jean-Eugène Piou</b>!</span></p>
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<span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif">Dirigé par le professeur associé à l’ISTEAH,
<b>Jean-Eugène Piou, ing., Ph.D.</b>, du Massachusetts Institute of Technology (MIT), le travail de recherche de deux étudiants de maîtrise de l’ISTEAH a fait l’objet de deux articles scientifiques dans une prestigieuse conférence de l’Institute of Electrical
 and Electronics Engineers (IEEE) à New York, du 26 au 29 novembre 2022. Toutes nos félicitations aux étudiants
<b>Wougens Vincent</b> (mathématiques) et <b>Amos Noël</b> (génie informatique), ainsi qu’au professeur
<b>Jean-Eugène Piou</b>!</span></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><u><span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif">Voici un résumé du premier article en question</span></u><span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif"> :</span></p>
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<b><span style="font-size:16.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">A Deep Learning Application to the 2004 Flooding of the City of Gonaïves in Haiti
</span></b></p>
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<span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Wougens Vincent<sup>1</sup>, Amos Noel<sup>1</sup> and Jean E. Piou<sup>2</sup>, Senior Member, IEEE
</span></p>
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<span style="font-family:"Arial",sans-serif;color:black">1: Graduate Student at <b>
Institut des Sciences, des Technologies et des Etudes Avancées d’Haïti (ISTEAH</b>), Saint-Marc, Haiti
</span></p>
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<span style="font-family:"Arial",sans-serif;color:black" lang="EN-CA">2: Research Scientist in Cambridge, MA, USA</span></p>
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<span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">In this paper, a deep learning network is considered to study the impact of the flooding on the city of Gonaives that occurred
 on 18 September 2004. Satellite images collected before and after the disaster are segmented then partitioned into 2 and 3 classes and later used to train and test the deep learning network, to estimate the damage that was inflicted upon the land topography
 and infrastructures of the city. Experiments conducted on the data revealed high performance of the network to identify areas buried in muddy water and regions of the city that did not suffer any damages. Data augmentation scenarios carried out on the training
 set translated into higher performance of the network on the test data than the result achieved when it was trained solely on the original images. The practicality of the deep learning to locate areas that were severely affected by the flood and estimate its
 impact on the residents of the city of Gonaïves is revealed.</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Published in: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black"><a href="https://ieeexplore.ieee.org/xpl/conhome/9965569/proceeding" target="_blank"><span style="color:#006699" lang="EN-CA">2022
 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)</span></a></span><br data-mce-bogus="1"></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Date of Conference: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">26-29
 October 2022</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Date Added to IEEE <i>Xplore</i>: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">01
 December 2022</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">ISBN Information:</span></b></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;background:white"><b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">DOI: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black"><a href="https://doi.org/10.1109/UEMCON54665.2022.9965684" target="_blank"><span style="color:#006699" lang="EN-CA">10.1109/UEMCON54665.2022.9965684</span></a></span><br data-mce-bogus="1"></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;background:white"><b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">Publisher: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">IEEE</span></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;background:white"><b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">Conference Location: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">New
 York, NY, NY, USA</span></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><u><span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif">Voici un résumé du deuxième article en question</span></u><span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif"> :</span></p>
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<h1 style="margin-top:0cm;text-align:center;background:white" align="center"><span style="font-family:"Arial",sans-serif;color:#333333" lang="EN-CA">Analyses of 2010 and 2021 Earthquakes that Struck Haiti Using a Deep Learning Network</span><span style="font-size:24.0pt;line-height:106%"></span></h1>
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<span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Wougens Vincent<sup>1</sup>, Amos Noel<sup>1</sup> and Jean E. Piou<sup>2</sup>, Senior Member, IEEE
</span></p>
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<span style="font-family:"Arial",sans-serif;color:black">1: Graduate Student at <b>
Institut des Sciences, des Technologies et des Etudes Avancées d’Haïti (ISTEAH</b>), Saint-Marc, Haiti
</span></p>
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<span style="font-family:"Arial",sans-serif;color:black" lang="EN-CA">2: Research Scientist in Cambridge, MA, USA</span></p>
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<span style="font-family:"Arial",sans-serif;color:black" lang="EN-CA"> </span></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;background:white"><b><span style="font-size:14.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">Abstract:</span></b></p>
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<span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">Presented in this paper are results from analyses conducted on satellite imagery collected on the 12 January 2010 earthquake with
 a moment magnitude (Mw) of 7.0 that devastated Port-au-Prince, the capital of Haiti, and the 14 August 2021 earthquake with moment magnitude (Mw) of 7.2 that struck the southwestern peninsula of Haiti. A deep learning network architecture that constitutes
 the main engine of this research investigation to carry out analyses from images collected before and after the earthquakes is considered. The images are segmented, labelled then randomly chosen to form training and testing datasets that are partitioned into
 3 classes. Localization of regions deeply affected by the impacts of the earthquakes and identification of land areas, road infrastructures and buildings severely damaged are useful information that the DL network provides to demonstrate its effectiveness.
 Data augmentation on the training side is considered to enhance the performance of the DL network on testing and shows its usefulness to reduce performance accuracy error and make the DL network a suited component in damage assessment. So, in the future, the
 DL network can integrate recovery and relief efforts as a tool that one can leverage on to limit the impacts of natural disasters on human lives.</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Published in: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black"><a href="https://ieeexplore.ieee.org/xpl/conhome/9965569/proceeding" target="_blank"><span style="color:#006699" lang="EN-CA">2022
 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)</span></a></span><br data-mce-bogus="1"></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Date of Conference: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">26-29
 October 2022</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Date Added to IEEE <i>Xplore</i>: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">01
 December 2022</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">ISBN Information:</span></b></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">DOI: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black"><a href="https://doi.org/10.1109/UEMCON54665.2022.9965694" target="_blank"><span style="color:#006699" lang="EN-CA">10.1109/UEMCON54665.2022.9965694</span></a></span><br data-mce-bogus="1"></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Publisher: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">IEEE</span></p>
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<b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black" lang="EN-CA">Conference Location: </span></b><span style="font-size:12.0pt;line-height:106%;font-family:"Arial",sans-serif;color:black;mso-fareast-language:FR-CA" lang="EN-CA">New
 York, NY, NY, USA</span></p>
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