We describe a method for computing visual correspondence based on the local ordering of intensities. Ordering information is robust to outliers and invariant to mono-tonic intensity distortions such as image gain. Our approach is based on non-parametric measures of association but also accounts for the spatial variation of disparities. We describe some of the mathematical properties of our algo...

The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. The good performance of the new test in detecting spatial causality and causal weighting matrix is notable and gives rise to an expectation that it may form a adequate tool for constructive specifica...

Accurate calibration of probabilistic predictive models learned is critical for many practical prediction and decision-making tasks. There are two main categories of methods for building calibrated classifiers. One approach is to develop methods for learning probabilistic models that are wellcalibrated, ab initio. The other approach is to use some post-processing methods for transforming the ou...

evaluation of river discharges trends is very important for water resources management and design of irrigation and drainage networks. in this research, annual, seasonal and monthly trends of maroon river discharge were evaluated using the mann-kendall and sen’s slope estimator non-parametric tests and the regression analysis parametric test. for this purpose, river discharge data from five h...