Spherea US (formerly Konrad Technologies USA), with ADS, G2CPU, and RADX Technologies, has developed an AI-based computer vision approach for testing EO sensors and cameras using NI (Emerson) hardware. The system enables automated, real-time anomaly detection that significantly improves coverage, repeatability, and reproducibility while reducing test costs in both engineering and production settings, even with multiple devices per station. Unlike conventional AI models requiring thousands of training images, this solution detects defects after only seconds of inline observation of known-good units. This makes it highly efficient and well-suited for scalable, production line applications.

• Learn how AI-based vision improves EO sensor defect detection with greater coverage, repeatability, and reproducibility.
• See how PXIe hardware and GPUs enable automated, high-throughput testing of multiple high-data-rate devices.
• Understand how minimal training data allows fast, scalable defect detection in production environments.