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The Rendered.ai Platform uses industry-standard models and techniques to create an unlimited of variety of synthetic imagery for AI training optimization.
The Rendered.ai Platform enables collaborative workflows between data science team members.
Rendered.ai's cloud-native platform enables rapid innovation by teams needing to generate and exploit synthetic datasets.
"Working with Rendered, we were able to use synthetic data to
significantly improve computer vision algorithm performance for
detecting economically important objects in satellite imagery. AP
scores improved across the board for identifying rare and unusual
objects when combining synthetic images with actual satellite
imagery compared with using real images alone. The objects in our
study have been historically difficult to identify using automated
algorithms but represent high value information for monitoring and
"We saw that synthetic data is a critical capability for computer vision algorithm development and for optimizing detection performance to extract vital information from real sensor-based data."
James Crawford, Orbital Insight
Founder, Chairman, CTO
Orbital Insight Technical Report
Using Synthetic Imagery to Train Detection Models of Rare Objects in Satellite Imagery
What "Synthetic Data" is in the context of AI, and why it's important for machine learning
Why we take a physics-based approach, and more about tools designed for Machine Learning Realism
What makes synthetic data “good”? We discuss repeatable, human understandable, closed-loop active learning workflows
A single easy-to-use tool for Synthetic data. Build a deeper understanding of outcomes with testable hypotheses on your data
Geo Week News, July 8, 2022
VentureBeat, June 1, 2022
Project GeoSpatial, May 11, 2022
AiThority, April 26, 2022
Geo Week News, April 21, 2022
Trajectory Magazine, April 8, 2022
ZDNet, February 3, 2022
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Geekwire, October 8, 2021
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TechCrunch, October 5, 2021
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BELLEVUE, Wash., October 6, 2020
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