Machine Learning Archives

Clouds overtop of the area labeled as clouds.

Three Lessons from Running an Imagery Labeling Competition

By Joe Morrison on October 9th, 2020

We joined with Radiant Earth at the Cloud Native Geospatial Sprint to run a labeling competition for non-technical folks. This resulted in over 2.3 million square kilometers mapped and lots of lessons learned.

Illustration of Raster Vision being used to find cars using machine learning.

Company

The Business Case for Raster Vision

By Joe Morrison on August 10th, 2020

Raster Vision is the interface between the fields of earth observation and deep learning, making it easier to apply novel computer vision techniques to geospatial imagery of all types. Joe lays out how it can be implemented in your organization and give you a competitive advantage.

Illustration of a clipboard overtop of labeled cars in a parking lot.

Software Engineering

3 Tips to Optimize Your Machine Learning Project for Data Labeling

By Niki LaGrone on July 21st, 2020

Mining the knowledge and expertise of your data labeling team will improve the data quality of your machine learning project and increase your team's productivity.

Software Engineering

SpaceNet Data Now Available in GroundWork

By Joe Morrison on June 12th, 2020

Incorporate high-resolution satellite imagery into your labeling projects for free.

Software Engineering

Image Classification Labeling: Single Class versus Multiple Class Projects

By Niki LaGrone on June 8th, 2020

When labeling for image classification is it faster to complete projects with single or multiple classes? We ran an experiment to find out.

Empty swingset overlaid with image of computer motherboard.

Software Engineering

Can AI Reduce Harm to Children?: Gabriel Fernandez and the Case for Machine Learning

By Niki LaGrone on April 9th, 2020

Could AI have saved Gabriel Fernandez’s life? Data and social scientists argue that machine learning might have kept him alive. What exactly is this potentially life-saving AI? Learn more about predictive risk modeling, how governments currently use similar AI, and the ethical questions such work raises.