03.12.21

New paper introduces a method to robustly homogenize data targeting COVID detection from CT images

The PrepNet neural network architecture homogenizes the appearance of CT images from different source datasets and hospitals so that more robust and trustworthy classifiers can be trained based on larger datasets.

23.11.21

How can kids learn so much faster than transformers?

Christoph von der Malsburg guest speaker at the CAI colloquium in Winterthur on November 17, 2021.

12.11.21

Bias, awareness, and ignorance in deep-learning-based face recognition

Humanity has developed successful approaches to overcome human biases. Our recent study shows why we need different approaches to reduce bias in machines.

21.10.21

ZHAW and Kistler team up to evaluate the possibilities of deep transfer learning for controlling injection molding processes

Researchers from the CAI and InES conduct a technical deep dive together to explore the possibilities of capturing process knowledge on injection molding in deep neural networks and transfer the results to novel usage scenarios.

08.10.21

TAILOR Scholarship for Mohammadreza Amirian, PhD Student at the Centre for Artificial Intelligence

Mohammadreza Amirian, researcher in the CAI’s Computer Vision, Perception and Cognition Group and doctoral student co-supervised by Friedhelm Schwenker of Ulm University and Thilo Stadelmann of the ZHAW, secured the first TAILOR Connectivity Fund…

31.03.21

ZHAW launches Centre for Artificial Intelligence

Machine Learning and Deep Learning have established themselves as major fields of research at the ZHAW School of Engineering. Scientific expertise around artificial intelligence is increasingly sought-after. By repositioning itself within the…