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School of Engineering

Intelligent Vision Systems Group

"We aim at advancing the state of the art in AI, Deep Learning and Machine Learning research, while at the same time developing tailored solutions to real-world challenging problems which help to advance technology and benefit humanity."

Dr. Frank-Peter Schilling

Fields of expertise

  • Computer Vision
  • Machine Learning Systems (MLOps)
  • Trustworthy and certifiable AI

We conduct research primarily in the domain of computer vision using 2-,3- or 4-D image or video data as input and performing classification, object detection or other visual tasks, for which we develop state of the art deep neural network architectures. We are particularly interested in recent developments including vision transformers and gauge equivariant neural networks. Domains of applications include, but are not limited to, industrial quality control, medical imaging and diagnosis (computed tomography), as well as earth (satellites) and sky (radio-astronomy) observation data. We are also interested in hybrid approaches to AI as well as geometric deep learning. Our second main area of interest concerns MLOps, which describes best practices for building complete, production-ready and scalable Machine Learning systems. Finally, we are interested in methods to create safe, trustworthy and certifiable AI systems, which comply with current and future legislation.

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Projects

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Publications