Raster Vision Archives | Page 3 of 10

Line chart that is going up with area underneath filled with a satellite image.

STAC Labeling Competition — Video Recap

By Joe Morrison on January 18th, 2021

Hear from labeling competition participants on why this diverse group of people came together, from across the world, to collaborate on a hallmark training dataset compliant with the STAC standard.

Chart for labeling project overlaid on image of a desk containing keyboard and clipboard.

Company

Managing Data Labeling for Machine Learning Projects

By Niki LaGrone on December 2nd, 2020

Responsible for the data labeling for a machine learning project? Here are some insights we’ve developed while managing data labeling for machine learning.

Clouds overtop of the area labeled as clouds.

Software Engineering

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

Introducing Raster Vision 0.12

By Lewis Fishgold on July 9th, 2020

We refactored the Raster Vision codebase from the ground up to make it simpler, more consistent, and more flexible. Check out Raster Vision 0.12.