Protostar Labs

Face detection using FPGA

This represents our pipeline to create a object detection model like Yolov3 with its implementation on edge device which in our case is FPGA. Throughout training, optimization and implementation of given model we deliver you a final model that runs on target device and performs Face Detection alongside results at which FPGA performs.

On-board anomaly detection on OPS-SAT satellite

Satellites need to constantly monitor their telemetry to make sure everthing is working as expected. Anomaly detection is a core functionaly needed for any mission to ensure the longevity of the satellite.

Classification of Multispectral Land Cover Images Using FPGAs

Creating an AI model that can utilize multispectral images for classification tasks for Earth observation is relatively simple. Creating an AI model that can be run on the satellite whilst adhering to power and resourse utilization is a whole other story.

SDK for AI model training and deployment to FPGAs

Satellites collect vast amounts of data that need to be processed and compressed before being downlinked to Earth. Advanced machine learning (ML) models have made sophisticated processing methods available, but utilizing these models requires domain-specific knowledge. The SDK addresses this by lowering the prerequisite knowledge needed to train, test, and deploy ML models onto resource-constrained platforms.