We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
In this paper we introduce a novel and simple image segmentation schemes that are based on combinations of morphological and statistical operations. Mathematical morphology is very...
Vakulabharanam Vijaya Kumar, B. Eswara Reddy, A. N...
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
This paper introduces a new approach to the problem of quantitative reconstruction of an object from few radiographic views. A mixed variable programming problem is formulated in ...
Mark A. Abramson, Thomas J. Asaki, J. E. Dennis, K...
— This work presents an automatic algorithm for extracting vectorial land registers from altimetric data in dense urban areas. We focus on elementary shape extraction and propose...