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.
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.
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.
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.
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.
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.