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<p class="MsoPlainText">Thiago Santos from the Brazilian Agricultural Research Corporation, Embrapa, will present a webinar, "Deep Learning and SfM: a promising framework for agricultural automation – an example with grapes (and some apples)," on Tuesday, December
10, 2019 at 3:00pm/15:00h BRT (UTC -3:00) as part of the IEEE RAS Technical Committee on Agricultural Robotics and Automation's (AgRA) webinar series.<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">Please register for this webinar here:<o:p></o:p></p>
<p class="MsoPlainText"><a href="https://zoom.us/webinar/register/3715750410413/WN_kS1zOuKbRn6l9wrjldAjIg">https://zoom.us/webinar/register/3715750410413/WN_kS1zOuKbRn6l9wrjldAjIg</a><o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">This webinar will also be broadcast with YouTube Live, which is an option from Zoom (registration not necessary if you are joining via YouTube Live).<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">Commenting and asking questions is still possible via YouTube Live. The link is not available beforehand, so check ~15 minutes before the webinar on Twitter, where I will post it publicly:<o:p></o:p></p>
<p class="MsoPlainText">https://twitter.com/AgRoboticsTC<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">All details, including a time zone converter, technical details, and presenter biography available here:<o:p></o:p></p>
<p class="MsoPlainText"><a href="http://ieeeagra.com/events/webinar-december-10-2019/">http://ieeeagra.com/events/webinar-december-10-2019/</a><o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">Title: Deep Learning and SfM: a promising framework for agricultural automation – an example with grapes (and some apples)<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">Abstract: Differently of industrial applications, agricultural environments lack structured spatial data and well-defined settings.
<o:p></o:p></p>
<p class="MsoPlainText">Such an environment is complex and presents large variations between fields and even intra-field, so intelligent systems are needed for its dynamic interpretation. For example, in fruit growing, not even the number and the placement
of fruits is known in advance, which imposes a challenge for any automation attempt. Fortunately, recent computer vision advances are able to automate the recovery of the 3-D structure of crop fields, by using techniques as structure-from-motion (SfM) and
SLAM, and detect and classify objects of interest, such as plants, leaves and fruits, by using state-of-the art techniques in machine vision such as Convolutional Neural Networks (CNNs). In this presentation, we will focus on wine grapes, a crop presenting
large variability in shape, color, and compactness. We can successfully detect grape clusters, and segment them using state-of-the-art CNNs. In a dataset containing 408 grape clusters from images taken on field, we have reached a F1-score up to 0.91 for instance
segmentation, a fine separation of each cluster from other structures in the image that allows a more accurate assessment of fruit size and shape. We will also show that clusters can be identified and tracked along video sequences recording orchards rows,
using 3-D information from a SfM system. We also will present a public dataset containing grape clusters properly annotated in 300 images and a novel annotation methodology for segmentation of complex objects in natural images. This computer vision pipeline
can be replicated for different crops and production systems, and we will present a preliminary work with apples to illustrate that such a pipeline can be employed on the development of sensing components for several agricultural and environmental applications.<o:p></o:p></p>
<p class="MsoNormal"><span style="font-family:"Book Antiqua",serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Book Antiqua",serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Book Antiqua",serif"><o:p> </o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">Amy Tabb Ph.D.<br>
Research Engineer<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black"><br>
United States Department of Agriculture,<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">Agricultural Research Service,<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">Appalachian Fruit Research Station<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black"><o:p> </o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">she/her<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">preferred address: Amy<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">if you really want to use a title and family name: Dr. Tabb<br>
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<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">Mailing:<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">USDA-ARS-AFRS<br>
2217 Wiltshire Rd<br>
Kearneysville, WV 25430<br>
304-725-3451 x386 office<br>
304-725-3451 x428 lab<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">304-620-5645 cell<br>
<a href="mailto:amy.tabb@usda.gov"><span style="color:#0563C1">amy.tabb@usda.gov</span></a><o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt;font-family:"Book Antiqua",serif;color:black">__________________________________________________________________<br>
While I check my email, I do so sparingly in order to be more productive while programming or writing and because I am frequently away from my desk. If you have an urgent email that requires a written response or have a time-sensitive topic to discuss, please
call the numbers above or have me paged. I typically work 7:30am-4pm ET (UTC -5:00).<o:p></o:p></span></p>
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