The Pattern Recognition Laboratory [PRLab] (part of the Pattern Recognition & Bioinformatics Group) is concerned with the classical trinity of representation, generalization, and evaluation, being the core elements of every pattern recognition system. The principal focus is on developing tools and theories and gaining knowledge and understanding applicable to a broad range of general problems but typically involving sensory data, e.g. times signals, images, video streams, or other physical measurement data. More specifically, the prominent research areas covered are dissimilarity-based pattern recognition, multiple classifier systems, and multiple instance learning, while increased interest goes to the investigation of alternative evaluation functions, e.g. ROC analyses, and fields like semi-supervised and active learning.