Victor Wåhlstrand Skärström

Doctoral Student at Signal Processing and Biomedical Engineering

Victor's research tries to combine the performance of modern methods of artificial intelligence in computer vision with explainability for critical applications such as healthcare. The overarching goal is to create trustable models for clinical professionals, working mostly with musculo-skeletal diseases such as osteoporosis. He has a special interest in uncertainty estimation, model calibration and out-of-distribution detection.

He has diverse experience of computer vision applications in the life sciences, materials science and digital humanities and has made various contributions to discourse analysis.

Source: chalmers.se

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2023

Convolution Neural Networks and Position Averaged Convergent Beam Electron Diffraction for Determining the Structure of 2D Materials

Andrew Yankovich, Magnus Röding, Victor Wåhlstrand Skärström et al

Microscopy and Microanalysis. Vol. 29 (1), p. 691-693

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