Raster Vision Archives | Page 8 of 8

Raster Vision: A New Open Source Framework for Deep Learning on Satellite and Aerial Imagery

By Rob Emanuele on October 18th, 2018

Azavea is pleased to announce the release of Raster Vision, a new open source framework for deep learning on satellite and aerial imagery.

Software Engineering

Predicting Land Use in the Amazon using Deep Learning

By Lewis Fishgold and Annie Zhao on January 3rd, 2018

Learn about our methods and results leveraging our RasterVision deep learning project to predict land use in satellite images of the Amazon.

Software Engineering

Serving Tiles with GeoTrellis, Lambda, and API Gateway

By James Santucci on October 30th, 2017

Have this open source serverless tile server built with the Serverless framework, AWS Lambda, AWS API Gateway, and GeoTrellis up and running in minutes.

Lewis Fishgold speaking about RasterVision at our Technical Staff Meeting

Software Engineering

Video: Using Convolutional Neural Networks to Automatically Analyze Aerial and Satellite Imagery

By Lewis Fishgold on September 6th, 2017

In this recording of our most recent Technical Staff Meeting, we walk through our team’s work on Raster Vision, a...

Deep Learning for Semantic Segmentation of Aerial Imagery by Azavea

Software Engineering

Deep Learning for Semantic Segmentation of Aerial and Satellite Imagery

By Lewis Fishgold and Rob Emanuele on May 30th, 2017

This post describes how to use deep learning to do semantic segmentation on aerial and satellite imagery, experiments on the ISPRS Potsdam dataset, and how to visualize model predictions on a map.

Software Engineering

Raster Foundry: Geospatial Analysis at Any Scale

By Joe Morrison on April 21st, 2017

Azavea has a rich history of productizing our research: from forecasting crime to managing green infrastructure in cities to aggregating...