We investigate the task of compressing an image by using different probability models for compressing different regions of the image. In an earlier paper, we introduced a class of...
Abstract. In this paper we introduce a new salient object segmentation method, which is based on combining a saliency measure with a conditional random field (CRF) model. The propo...
Esa Rahtu, Juho Kannala, Mikko Salo, Janne Heikkil...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
A fractional Fourier transform (FrFT) based estimation method is introduced in this paper to analyze the long range dependence (LRD) in time series. The degree of LRD can be chara...