Raster Vision Archives | Page 2 of 3

Betting Big on the Spatiotemporal Asset Catalog (STAC) Standard

By Joe Morrison on November 22nd, 2019

We're investing heavily in the STAC specification - including building a STAC-compatible Python library and server as well contributing to the Label Extension. We're hoping this work will help accelerate adoption across the geospatial engineering community more broadly.

Screenshot of labeled satellite imagery in Raster Vision.

Company

An Introduction to Satellite Imagery and Machine Learning

By Joe Morrison on November 5th, 2019

Today, the availability of satellite imagery still far outpaces our capacity to analyze it, but machine learning and tools like Raster Vision are helping.

Satellite imagery displaying machine learning labels.

Software Engineering

Azavea and CloudFactory: Partners on Quality Training Data and Social Impact

By Joe Morrison on October 8th, 2019

Read about our journey to hiring an outsourced data labeling firm and how we’ve found a partner in CloudFactory.

Software Engineering

STAC: Creating an Ecosystem of SpatioTemporal Assets

By Niki LaGrone, James Santucci and Aaron Su on October 1st, 2019

STAC is creating an ecosystem of interoperable spatiotemporal assets. Learn how Azavea has contibuted and about future steps for the specification.

Company

Is This a Crosswalk?: 5 Takeaways from Training a Data Labeling Team

By Niki LaGrone on September 13th, 2019

We trained remote computer vision workers to provide data labeling for machine learning projects. Here's what we learned.

Ground truth imperfectly overlaying machine learning predictions.

Software Engineering

Using Noisy Labels to Train Deep Learning Models on Satellite Imagery

By Lewis Fishgold on August 5th, 2019

How do noisy labels affect the accuracy of a deep learning model? We added different amounts of noise to the SpaceNet Vegas buildings dataset and trained some models to find out.