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    <font class="" face="Cambria"><font class="" style="font-size:
        14px;">1st International Workshop in <b>Deep Learning for
          Activity Monitoring</b> (DLAM 2019)</font></font>
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      <p style="background-color: rgb(255, 255, 255);" class=""><font
          class="" face="Cambria"><font class="" style="font-size:
            14px;">Taipei - TAIWAN, September 21st 2019</font></font></p>
      <p style="background-color: rgb(255, 255, 255);" class=""><font
          class="" face="Cambria"><font class="" style="font-size:
            14px;">In conjunction with (<b>AVSS 2019</b>) - 16th IEEE
            International Conference on Advanced Video and Signal-based
            Surveillance </font></font></p>
      <p style="background-color: rgb(255, 255, 255);" class=""><font
          class="" face="Cambria"><font class="" style="font-size:
            14px;">Workshop Website: </font><span class=""
            style="font-size: 14px;"> </span><span class=""
            style="font-size: 14px;"><a
              href="http://dlam2019.isasi.cnr.it/home/" class=""
              moz-do-not-send="true">http://dlam2019.isasi.cnr.it/home/</a></span></font></p>
      <p style="background-color: rgb(255, 255, 255);" class=""><font
          face="Cambria">---<br>
          <font size="-1">Note: the Workshop will be organized
            back-to-back with the IEEE <b>International Conference on
              Image Processing (ICIP)</b> 2019, which is also held in
            Taipei from 9/22 to 9/25. Attendants will be able to
            conveniently attend two leading computer vision/image
            processing conferences and their workshops in a single trip
            to Taiwan!<br>
            ---</font></font><br>
        <font class="" face="Cambria"><span class="" style="font-size:
            14px;"></span></font></p>
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          </font></div>
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            class="" style="font-size: 14px;" face="Cambria">*****************************<br
              class="">
            IMPORTANT DATES<br class="">
            ******************************<br class="">
            <br class="">
            <u>Submission deadline: </u><u><b>July 6th</b></u><u> 2019</u><br
              class="">
            Paper acceptance notification: July 14th 2019<br class="">
            Camera ready: July 29th 2019<br class="">
            <br class="">
            *************************<br class="">
            CALL FOR PAPERS<br class="">
            *************************<br class="">
            <br class="">
            In last decade, Deep Learning has become the most used
            approach to any computer vision problem; on the other hand,
            there has been a growing diffusion of many different kind of
            sensing device (static and mobile) for environmental
            monitoring and surveillance purposes. <br class="">
            The focus of the Workshop is on the application of Deep
            Learning approaches to the activity recognition, with
            special attention to real applications in real contexts. <br
              class="">
            We encourage researchers to formulate innovative feature
            representations, learning methodologies, and end-to-end
            vision systems based on deep learning. Aim of this workshop
            is to bring together researchers from different communities
            (such as Computer Vision, networked embedded sensing,
            artificial intelligence and so on) which address both the
            main topics of Deep Learning and Activity Recognition.<br
              class="">
            <br class="">
          </font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria">- Single
            and multiple object tracking</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
          </font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria">-
            Re-identification</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Human behavior analysis</font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Deep Learning in embedded systems</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Deep Learning for crowd analysis </font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Individual activity detection and recognition</font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Multi-agent/multi sensing activity detection and
            recognition</font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Scene understanding</font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Sensor calibration</font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Event detection</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
            - Real time applications</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
          </font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria">-
            Advancements in deep learning</font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><br>
          </font></div>
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          <u><font class="" style="font-size: 14px;" face="Cambria"><font
                color="#000000"><font size="+1">Note that accepted
                  papers will be published in the Main Conference
                  proceedings.</font><br>
              </font></font></u><font size="-1" face="Cambria"
            color="#000000"><br>
          </font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            size="-1" face="Cambria" color="#000000">Please visit our
            Workshop website  </font><font size="-1" face="Cambria"
            color="#000000"><a href="http://dlam2019.isasi.cnr.it/home/"
              moz-do-not-send="true">http://dlam2019.isasi.cnr.it/home/</a>
            for information about DLAM 2019, while more details about
            the Main Conference can be found at </font><font size="-1"
            face="Cambria" color="#000000"><a
              href="http://avss2019.org/" moz-do-not-send="true">http://avss2019.org/</a></font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
          </font></div>
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            class="" style="font-size: 14px;" face="Cambria"><br
              class="">
          </font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><font
              class="" style="font-size: 14px;" face="Cambria">*************************<br
                class="">
            </font></font><font class="" style="font-size: 14px;"
            face="Cambria"><font class="" style="font-size: 14px;"
              face="Cambria"><font class="" style="font-size: 14px;"
                face="Cambria">INVITED SPEAKERS</font></font></font></div>
        <div class="" style="background-color: rgb(255, 255, 255);"><font
            class="" style="font-size: 14px;" face="Cambria"><font
              class="" style="font-size: 14px;" face="Cambria">*************************</font></font></div>
        <br>
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            67, 70);"><font class="" face="Cambria"><font class=""
                style="font-size: 14px;"> </font><span class=""
                style="font-size: 14px; font-style: inherit;
                font-variant-caps: inherit;"><b class="">Jeff Alstott –
                  IARPA </b></span></font></div>
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            currentcolor; vertical-align: baseline; caret-color: rgb(51,
            67, 70);"><span class="" style="font-size: 14px; font-style:
              inherit; font-variant-caps: inherit;"><font class=""
                face="Cambria"><br class="">
              </font></span></div>
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            currentcolor; vertical-align: baseline; caret-color: rgb(51,
            67, 70);"><span class="" style="text-align: justify;
              font-size: 14px;"><font class="" face="Cambria">Dr. Jeff
                Alstott is a program manager at IARPA. He previously
                worked for MIT, Singapore University of Technology and
                Design, the World Bank and the University of Chicago. He
                obtained his PhD studying complex networks at the
                University of Cambridge, and his MBA and bachelor’s
                degrees from Indiana University. He has published
                research in such areas as animal behavior, computational
                neuroscience, complex networks, design science,
                statistical methods, and S&T forecasting.</font></span></div>
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              </font></span></div>
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            baseline; caret-color: rgb(51, 67, 70); color: rgb(51, 67,
            70);"><font color="#000000"> </font><br>
            <div class="">
              <div class="" style="caret-color: rgb(0, 0, 0); color:
                rgb(0, 0, 0);">
                <div class="" style="background-color: rgb(255, 255,
                  255);"><font class="" style="font-size: 14px;"
                    face="Cambria"><font class="" style="font-size:
                      14px;" face="Cambria">*************************<br
                        class="">
                    </font></font><font class="" face="Cambria"><span
                      class="" style="font-size: 14px;">ORGANIZERS</span></font></div>
                <div class="" style="caret-color: rgb(0, 0, 0); color:
                  rgb(0, 0, 0);"><font class="" style="font-size: 14px;"
                    face="Cambria"><font class="" style="font-size:
                      14px;" face="Cambria">*************************</font></font><font
                    class="" face="Cambria"><span class=""
                      style="font-size: 14px;">               <br>
                    </span></font></div>
              </div>
            </div>
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            padding: 0px; border: 0px; outline: 0px; vertical-align:
            baseline; caret-color: rgb(51, 67, 70); color: rgb(51, 67,
            70);"><span class="" style="text-align: justify; font-size:
              14px;"><font class="" face="Cambria"><br class="">
              </font></span></div>
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            padding: 0px; border: 0px; outline: 0px; vertical-align:
            baseline;"><span class="" style="text-align: justify;"><font
                class="" face="Cambria"><font class="" color="#334346"><span
                    class="" style="font-size: 14px;"><font class=""
                      color="#000000"><b class="">Rama Chellappa</b></font>,
                    <font color="#000000">University of
                      Maryland, College Park, USA</font></span></font></font></span></div>
          <div class="" style="box-sizing: border-box; margin: 0px;
            padding: 0px; border: 0px; outline: 0px; vertical-align:
            baseline; caret-color: rgb(51, 67, 70); color: rgb(51, 67,
            70);"><span class="" style="text-align: justify; font-size:
              14px;"><font class="" face="Cambria"><br class="">
              </font></span></div>
          <div class="" style="box-sizing: border-box; margin: 0px;
            padding: 0px; border: 0px; outline: 0px; vertical-align:
            baseline; caret-color: rgb(51, 67, 70); color: rgb(51, 67,
            70);"><font class="" face="Cambria"><span class=""
                style="text-align: justify; font-size: 14px;"><font
                  class=""><b class="">P</b></font></span><span class=""
                style="font-size: 14px; caret-color: rgb(0, 0, 0);
                color: rgb(0, 0, 0);"><b class="">ier Luigi Mazzeo</b>,
                CNR-Institute of Applied Sciences and Intelligent
                Systems, IT</span></font></div>
          <div class="">
            <pre class=""><pre class=""><span class="" style="font-size: 14px;"><font class="" face="Cambria"><b class="">Paolo Spagnolo</b>, CNR-Institute of Applied Sciences and Intelligent Systems, IT</font></span></pre><pre class=""><span class="" style="font-size: 14px;"><font class="" face="Cambria"><b class="">Lei Zhang,</b>  Microsoft AI & Research, USA</font></span></pre><span class="" style="font-size: 14px;"><font class="" face="Cambria">
</font></span><pre class=""><div class="" style="white-space: normal; box-sizing: border-box; margin: 0px; padding: 0px; border: 0px; outline: 0px; vertical-align: baseline; caret-color: rgb(51, 67, 70); color: rgb(51, 67, 70);"><div class="" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><font class="" style="font-size: 14px;" face="Cambria"><font class="" style="font-size: 14px;" face="Cambria">*************************</font></font></div><div class="" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><font class="" face="Cambria"><span class="" style="font-size: 14px;">CONTACTS</span></font></div><div class="" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><font class="" style="font-size: 14px;" face="Cambria"><font class="" style="font-size: 14px;" face="Cambria">*************************</font></font></div></div></pre><pre class=""><font class="" face="Cambria"><span class="" style="font-size: 14px; white-space: normal;">email: <a href="mailto:wdlam@gmail.com" class="" moz-do-not-send="true">wdlam2019@gmail.com</a></span></font></pre><pre class=""><span class="" style="white-space: normal; font-size: 14px;"><font class="" face="Cambria">website: <a href="http://dlam2019.isasi.cnr.it/home/" class="" moz-do-not-send="true">http://dlam2019.isasi.cnr.it/home/</a></font></span></pre><div class="">
</div></pre>
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