3 citations · 4 across the 3 of their papers we have counts for
4 papers
When Data do not Bring Information: A Case Study in Markov Random Fields Estimation
J. Gimenez, A. C. Frery, Ana Georgina Flesia
The Potts model is frequently used to describe the behavior of image classes, since it allows to incorporate contextual information linking neighboring pixels in a simple way. Its…
Accuracy of MAP segmentation with hidden Potts and Markov mesh prior models via Path Constrained Viterbi Training, Iterated Conditional Modes and Graph Cut based algorithms
Ana Georgina Flesia, Josef Baumgartner, Javier Gimenez +1
In this paper, we study statistical classification accuracy of two different Markov field environments for pixelwise image segmentation, considering the labels of the image as hidd…
Markovian models for one dimensional structure estimation on heavily noisy imagery
Ana Georgina Flesia, Javier Gimenez, Elena Rufeil Fiori
Radar (SAR) images often exhibit profound appearance variations due to a variety of factors including clutter noise produced by the coherent nature of the illumination. Ultrasound…
Unsupervised edge map scoring: a statistical complexity approach
Javier Gimenez, Jorge Martinez, Ana Georgina Flesia
We propose a new Statistical Complexity Measure (SCM) to qualify edge maps without Ground Truth (GT) knowledge. The measure is the product of two indices, an \emph{Equilibrium} ind…