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(This article was first published on <strong><a href="http://www.bnosac.be/index.php/blog/66-computer-vision-algorithms-for-r-users"> bnosac :: open analytical helpers</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Just before the summer holidays, BNOSAC presented a talk called <span>Computer Vision and Image Recognition algorithms for R users</span> at the UseR conference. In the talk 6 packages on Computer Vision with R were introduced in front of an audience of about 250 persons. The R packages we covered and that were developed by BNOSAC are:</p>
<ul>
<li>image.CornerDetectionF9:  FAST-9 corner detection</li>
<li>image.CannyEdges: Canny Edge Detector</li>
<li>image.LineSegmentDetector: Line Segment Detector (LSD)</li>
<li>image.ContourDetector:  Unsupervised Smooth Contour Line Detection</li>
<li>image.dlib: Speeded up robust features (SURF) and histogram of oriented gradients (FHOG) features</li>
<li>image.darknet: Image classification using darknet with deep learning models AlexNet, Darknet, VGG-16, GoogleNet and Darknet19. As well object detection using the state-of-the art YOLO detection system</li>
</ul>
<p>For those of you who missed this, you can still see the video of the presentation &amp; view the pdf of the presentation below. The packages are open-sourced and made available at <a rel="nofollow" href="https://github.com/bnosac/image" target="_blank">https://github.com/bnosac/image</a></p>
<p><iframe width="450" allowfullscreen src="https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Computer-Vision-and-Image-Recognition-algorithms-for-R-users/player"></iframe></p>
<p>If you have a computer vision endaveour in mind, feel free to <a rel="nofollow" href="http://www.bnosac.be/index.php/contact/get-in-touch" target="_blank">get in touch for a quick chat</a>. For those of you interested in following training on how to do image analysis, you can always register for our <a rel="nofollow" href="https://lstat.kuleuven.be/training/coursedescriptions/ComputervisionwithRandPython" target="_blank">training on Computer Vision with R and Python here</a>. More details on the full training program and training dates provided by BNOSAC: visit <a rel="nofollow" href="http://bnosac.be/index.php/training" target="_blank">http://bnosac.be/index.php/training</a></p>
<p>{aridoc engine=”pdfjs” width=”100%” height=”450″}images/bnosac/blog/presentation-user2017.pdf{/aridoc}</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.bnosac.be/index.php/blog/66-computer-vision-algorithms-for-r-users"> bnosac :: open analytical helpers</a></strong>.</div>
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