Research Group Neuromorphic Computing
The Neuromorphic Computing Group develops advanced neural-network based algorithms, software libraries, and systems with the new generation of computing chips – brain-inspired neuromorphic sensing and computing hardware. We focus on perception, motion planning, and control for robotic actuators with applications in life sciences: healthcare, agriculture, food processing, and smart environments. We follow a human-centered design approach to develop new generation of physical AI systems that are power-efficient, adaptive, and safe.
- Neuromorphic computing hardware and algorithms
- Event-based vision
- Robotics: Motion planning, control, SLAM
- Efficient machine learning and AI
- Dynamical systems, cognitive architectures
- Assistive robotics in healthcare, agriculture, food processing, smart environments
- Machine vision in healthcare, agriculture, food processing, smart environments
- Continual learning and adaptive systems
- Robot safety, human-robot interaction
Transformer Networks for Drone Signals
Shapescience – AI for morpholigcally based fruit variety recognition
Pomological and molecular genetic methods have been the tools of choice to describe fruit varieties and their characteristics. Thanks to the possibility of using 3D scanning technology and machine learning, there is a revival of phenotyping, i.e. the typification of fruits based on their appearance. The Shapescience ...