“Azavea built a highly scalable and robust machine learning pipeline that allows us to produce high accuracy, high resolution cropland maps for all of Ghana. Their effort in developing this went far above and beyond what we all initially imagined would be the scope of effort, and is a really critical contribution to our project’s success.”
“Azavea has been a great partner in developing a web-based decision support tool that presents complex spatial information to water utility technicians in a simple, usable format. Together, we’re helping keep drinking water safe.”
Our customers upload thousands of images per day. Raster Foundry allows them to process remotely sensed data rapidly to create maps and custom analysis seamlessly.
The biggest obstacle to leveraging machine learning is the absence of high-quality training data. Our clients can label and validate images quickly, manage large queues, and improve model performance easily. Or you can leave the work to us.
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Using Raster Vision, our open source library for applying computer vision and machine learning techniques to Earth observation imagery, Raster Foundry can perform object detection, chip classification, semantic and instance segmentation operations.
We've built custom internal business process applications for some of our larger clients. We serve as trusted consultants and long-term maintainers.
Every labeling project begins with good imagery. In our latest white paper, we discuss cost, resolution, update frequency, third party vendors, and more. Read our free white paper to discover the best satellite imagery for your project.
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