A major industrial components manufacturer entrusted Auriga with modernization of the legacy anomaly detection system that sorts out defective parts on the production line.
Parallel data analysis increased overall performance up to 30% .
In-built OpenVINO optimizing tool leveraged to accelerate trained models for better performance.
Automated self-test and diagnostic tools implemented to maintain high level of safety and reliability.
The overall analysis module performance was increased up to 40% by the proposed approach and architecture design.
Developed web-based tool allows to swiftly upgrade algorithm upon launch of any new types of production.
Intel OpenVINO · Keras · XGBoost · GStreamer · CUDA · MS SQL Server
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