[MATLAB Webinars] Upcoming Academic Sessions – January 2015

Join us online to learn more about MATLAB and Simulink. Each live webinar is free and features application demonstrations followed by a Q&A session with a MathWorks Engineer.


Parallel Computing with MATLAB
January 9, 2015
Session 1:  2 pm // Session 2:  7 pm

Learn how you can use Parallel Computing Toolbox and MATLAB Distributed Computing Server to speed up MATLAB applications by using the desktop and cluster computing hardware you already have. You will learn how minimal programming efforts can speed up your applications on widely available desktop systems equipped with multicore processors and GPUs, and how to continue scaling your speed up with a computer cluster.


Introduction to Geospatial (Mapping) Analysis using MATLAB
Date: January 16, 2015
Session 1:  2 pm // Session 2:  7 pm

This session provides an overview of using MATLAB for geospatial image and data analysis. Using imagery acquired from USGS Web Services, we will demonstrate the development and application of an algorithm to quantify from aerial imagery the portion of land under irrigation.

This session is intended for anyone interested in using MATLAB to analyze geospatially-oriented data.

Highlights include:

  • Accessing aerial NAIP (National Agriculture Imagery Program) imagery from a web map server
  • Developing an algorithm to detect and differentiate irrigation crop circles
  • Automating the algorithm over a range of sub-images
  • Displaying results on a map axis
  • Generating reports on the results

Additionally, we will demonstrate the registration of aerial images and the positioning of cellular towers to optimize coverage.

Highlights include:

  • Downloading digital elevation model and aerial imagery using WMS
  • Annotating terrain data with contour lines, colormaps, and more
  • Calculating line-of-sight visibility, and viewshed


Computer Vision Made Easy
Date: January 27, 2015
Session 1:  2 pm // Session 2:  7 pm

In this webinar you will learn how to use computer vision algorithms to solve real world imaging problems. Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene.

You will discover how to:

  • Find moving objects in video
  • Analyze the motion of objects
  • Detect and locate faces in images and video
  • Track a single object over many frames of video

We will demonstrate key features through real world examples including:

  • Analyzing the flow of traffic using motion analysis
  • Using a person’s movements to interact with a computer
  • Locating an object in a cluttered scene

This webinar assumes some experience with MATLAB and no experience with computer vision. We will focus on the Computer Vision System Toolbox.

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