Raster Foundry Archives

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.

Screenshot of command line implementation.

Software Engineering

Notifications over Websockets with Http4s and Skunk

By James Santucci on May 20th, 2020

In an attempt to avoid relying on polling in a front-end application or third-party services, we attempt servicing asynchronous notifications over websockets using only PostgreSQL and Scala.

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.

Application screenshot of labeled satellite imagery.

Software Engineering

Labeling Satellite Imagery for Machine Learning

By Niki LaGrone on March 24th, 2020

Definitions and visuals of the most common ways to label satellite imagery for machine learning. Includes tips for managing annotations for each type.

Ground truth and model prediction outlines overlaying the original geospatial chip.

Company

Join the OpenCities AI Challenge and Detect Building Footprints from Aerial Imagery

By Simon Kassel on January 16th, 2020

We partnered with Driven Data and the World Bank to develop the Open Cities AI Challenge. This challenge uses machine learning to extract building footprints in unmapped areas to promote disaster resilience.

Slider for testing seams of labeled machine learning data.

Software Engineering

3 Ways to Analyze the Results of a Supervised Machine Learning Model

By Joe Morrison on December 13th, 2019

How accurate are our supervised machine learning models and what are they really doing? We offer 3 tips to help you better understand these models.