Fully opened industrial gates cause unnecessary energy loss. Together with Bircher Smart Access, SCS developed Hyperion 3D, a stereoscopic image processing system that opens gates only as high as necessary and closes them again as early as possible.
In the semiconductor industry, leaky pipe connections can cause enormous damage. SCS developed an image-based inspection method for Georg Fischer that automatically assesses the quality of weld seams.
The Danish railway Banedanmark needs to digitize over 10,000 cable diagrams; purely manual entry would take years. SCS won the international competition for ideas with a concept designed to automate large parts of this work using learning systems.
Undetected hip malalignments in newborns can necessitate extensive treatment later in life. SCS developed deep learning algorithms that objectively determine the Graf alpha angle in ultrasound images of infant hips and support physicians in their assessment.
Counting cells in microscopy images was previously a time-consuming manual process. SCS developed a deep-learning algorithm that automatically counts cells and delivers fast, reliable results even on a standard lab PC.
Optical coherence tomography provides high-resolution 3D images of the eye. SCS developed an AI model for the automated segmentation of medically relevant structures in OCT scans. In a scientific study, the accuracy of the eye segmentation proved to be comparable to human evaluations.
Confidential conversations such as interrogations, hearings, and examinations can be transcribed and translated in real-time with SCS Evida. Processing occurs locally rather than in the cloud, ensuring sensitive data remains within the organization.
Wheel defects, such as flat spots, strain railway infrastructure and cause noise. SCS developed algorithms for SBB that detect such damage from the measurement signals of wheel load checkpoints and, in some cases, also determine their severity, allowing affected vehicles to be specifically repaired.
SCS developed a machine learning model for SBB that identifies imminent stuck brakes based on consecutive HFO measurements before the alarm threshold is reached, enabling targeted interventions.
SCS developed an explainable machine learning algorithm for SBB that calculates the forces between wheel and rail from acceleration sensors on the bogie, eliminating the need for maintenance-intensive sensors on the rotating wheels.
Copyright 2026 © SCS · Supercomputing Systems AG. All rights reserved. Website created by hhomepage Web Agency - Imprint - Privacy Policy
