Niclas Ståhl

Assistant Professor
Department of Computing , School of Engineering

Article

Ståhl, N., Weimann, L. (2022). Identifying wetland areas in historical maps using deep convolutional neural networks Ecological Informatics, 68. More information

Conference paper

Ståhl, N., Mathiason, G., Bae, J. (2022). Utilising Data from Multiple Production Lines for Predictive Deep Learning Models. Cham: Springer, 18th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2021, Salamanca, 6 October 2021 - 8 October 2021, 264809. More information
Johansson, U., Löfström, T., Ståhl, N. (2022). Well-Calibrated Rule Extractors. 11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK. More information