Deep Learning Applications for Geospatial Data:
A Hands-On Workshop

— THE DECEMBER WORKSHOP IS NOW FULL —

Registration for January now open

An example application: Identifying cars in aerial imagery:

Register

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About This Workshop

AI is transforming business in every sector. We frequently hear the terms “AI”, “machine learning”, and “deep learning” in the news these days, but many of us are not familiar with this technology nor do we understand how it will impact our work.

In this workshop, we will help you understand the fundamentals of deep learning and show you how  it can be applied to geospatial data using two examples: identifying objects in imagery and classifying point cloud data. We will give you some useful tips as you go “hands-on” with sample data to create your own training data, train your own deep learning model, and then evaluate your model.

This workshop is led by Solv3D, leaders in providing geospatial applications including a deep learning toolkit for practitioners.

Who Should Attend

Anyone with experience in geospatial data but has no background in deep learning and who wants to learn about how this exciting new technology can be used on geospatial data. Begin your deep learning journey here!

Anyone with a deep learning background and who is also familiar with geospatial data, but would like to explore our unique deep learning tool kit is also welcome to attend. See the unique benefits of our deep learning tool kit!

Dates, Location, and Duration

— THE DECEMBER WORKSHOP IS NOW FULL —

We will hold this workshop on the first Tuesday of every month at 0800 Calgary time (Mountain Standard Time). This is a 4-hour, intensive workshop, which is why there is an early start.

This will be an online workshop.

Outline

Introduction to Deep Learning

• What is deep learning?
• A typical workflow using deep learning technology to identify objects.
• Issues to be aware of when using deep learning technology.
• Options for deep learning tools.

Applying Deep Learning to Geospatial Data

• Example 1: Using deep learning to identify objects in aerial (orthomosaic) imagery
  • Workflow
  • Tips
  • Hands-on training a model
  • Hands-on using a model
• Example 2: Using deep learning to identify objects in panoramic (scene view) imagery
  • Workflow
  • Tips
  • Hands-on training a model
  • Hands-on using a model
• Example 3: Using deep learning to classify point cloud data
  • Workflow
  • Tips
  • Hands-on training a model
  • Hands-on using a model

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