Raster Vision Archives | Page 2 of 7

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.

Person walking down city park in the fall.

Software Engineering

America’s Cities are Sitting on a Gold Mine of Machine Learning Training Data

By Joe Morrison on February 2nd, 2020

Cities may not know it, but by nature of collecting and maintaining various datasets, they are sitting on a treasure trove of machine learning-ready training data.

Letters AMA on top of aerial earth imagery.

Software Engineering

The Future of Machine Learning AMA

By Lewis Fishgold, James McClain and Rob Emanuele on January 31st, 2020

3 of our machine learning engineers answer your questions about the future of machine learning.