New methods of machine learning and artificial intelligence, combined with precise real-time tracking, allow a new depth of game and training analysis.
Automated action recognition in combination with machine learning and hierarchical event recognition allows the automatic generation of game statistics.
Real-time analysis of soccer players' performance and the course of play using cost-effectiv sensors and machine learning to detect speeds, actions and events for trainers and players.
Real-time measurements of the acceleration curve and speed of punches using specially developed miniaturized sensor technology in combination with sensor-based artificial intelligence.
Fast sports-scene search engine. Based on deep learning, our S3Engine technology enables fast searches for similar game scenes in sports, evaluates them and suggests solutions.
The retrofittable and intelligent sensor module for hand tools measures various parameters in manual work processes and thus enables process optimization.
In the QuaST research project, Fraunhofer IIS is developing the necessary software and services to enable or facilitate the use of currently available and future quantum computers by academic and industrial users.
In the QLindA project (Quantum Reinforcement Learning for Industrial Applications), we are developing novel algorithms with partners to transfer reinforcement learning approaches to high-performance quantum computers.
Fraunhofer Institute for Integrated Circuits IIS