Introducing: Raster Vision v0.20
By Adeel Hassan on January 5th, 2023
We outline Raster Vision V0.20, introducing new features, improved documentation, and an entirely new way to use the project.
Automated Building Footprint Extraction (Part 2): Evaluation Metrics
By Lewis Fishgold on November 1st, 2022
In the second part of our Automated Building Footprint Extraction series, we review some evaluation metrics for building footprint extraction.
A Human-in-the-Loop Machine Learning Workflow for Geospatial Data
By Adeel Hassan on September 28th, 2022
In this blog we demonstrate how an active learning approach can boost machine learning model performance with the human-in-the-loop workflow.
Change detection with Raster Vision
By Adeel Hassan on April 18th, 2022
This blog explores the direct classification approach to change detection using our open-source geospatial deep learning framework, Raster Vision, and the publicly available Onera Satellite Change Detection (OSCD) dataset.
Introducing Raster Vision 0.13
By Adeel Hassan on April 26th, 2021
This release presents a major jump in Raster Vision's power and flexibility. The newly added features allow for finer control of the model training as well as greater flexibility in ingesting data.
The Business Case for Raster Vision
By Joe Morrison on August 10th, 2020
Raster Vision is the interface between the fields of earth observation and deep learning, making it easier to apply novel computer vision techniques to geospatial imagery of all types. Joe lays out how it can be implemented in your organization and give you a competitive advantage.