Statistical Image Analysis and Learning

Markov field models for image enhancement, segmentation, edge detection, reconstruction from projections and nervous systems. Image recognition using neural networks. Random numer generators and simulated annealing. Examples from medical image diagnosis and neuro-modelling.

To acquire basic knowledge in image processing and learning in neural networks.

Lectures and exercises. Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam (75%) and two exercises (25%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may change from written to oral.