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.
Skin Tone Estimation
This system for skin tone estimation is a useful tool for beauty products recommendation. In addition to the estimation model itself, the system contains image preprocessing tools which makes it robust in all lighting environments.
Causal inference for root cause analysis in biotech
On top of its anomaly detection abilities AnomalAIzer offers state or art causal inference engine with ability to analyze complex multi-variate data streams enabling real-time tracking and response to data changes.
Anomaly detection in multivariate data streams
AnomalAIzer is an advanced machine learning platform that allows to monitor and analyze complex multi-variate data streams. It offers real-time anomaly detection and visualization providing insight to workers in various scientific and industrial fields.
Enhancing RGB images with multispectral data
Our deep learning model brings multi spectral data to standard RGB images, providing valuable spectral information without the need for expensive specialized cameras.
Vision-based On-Orbit Inspection for Optimal Solar Panel Deployment
Multispectral cameras are expensive and hard to acquire, especially the ones with proven flight herritage. Creating a module that enables multispectral measurements would help bridge the gap between functionality and cost-awareness.
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.
Visual Quality Inspection of Lanterns
The application of artificial intelligence and computer vision in an industry such as the lantern industry has many benefits, some of which are time reduction, increase in product quality and safety.
Visual Quality Inspection of Bottle Packaging
Using machine learning and computer vision we can detect defects in various bottle formats while integrating seamlessly with existing production lines. This system offers high accuracy, low false positives, unmatched processing speed effictively increasing efficiency and reducing cost.