Many of the same modeling methods used in natural languages, speci cally Markov models and HMM's, have also been applied to biological sequence analysis. In recent years, nat...
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...
Robert C. Williamson, Alex J. Smola, Bernhard Sch&...
Abstract. This paper presents a novel approach to unsupervised texture segmentation that relies on a very general nonparametric statistical model of image neighborhoods. The method...
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
In this paper we show how genetic programming can be used to discover useful texture feature extraction algorithms. Grey level histograms of different textures are used as inputs ...