The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

Currently displaying 1 – 2 of 2

Showing per page

Order by Relevance | Title | Year of publication

Wildfires identification: Semantic segmentation using support vector machine classifier

Pecha, Marek;  Langford, Zachary;  Horák, David;  Tran Mills, Richard — 2023

Programs and Algorithms of Numerical Mathematics

This paper deals with wildfire identification in the Alaska regions as a semantic segmentation task using support vector machine classifiers. Instead of colour information represented by means of BGR channels, we proceed with a normalized reflectance over 152 days so that such time series is assigned to each pixel. We compare models associated with 𝓁 1 -loss and 𝓁 2 -loss functions and stopping criteria based on a projected gradient and duality gap in the presented benchmarks.

Parallel strategies for solving the FETI coarse problem in the PERMON toolbox

Vašatová, Alena;  Tomčala, Jiří;  Sojka, Radim;  Pecha, Marek;  Kružík, Jakub;  Horák, David;  Hapla, Václav;  Čermák, Martin — 2017

Programs and Algorithms of Numerical Mathematics

PERMON (Parallel, Efficient, Robust, Modular, Object-oriented, Numerical) is a newly emerging collection of software libraries, uniquely combining Quadratic Programming (QP) algorithms and Domain Decomposition Methods (DDM). Among the main applications are contact problems of mechanics. This paper gives an overview of PERMON and selected ingredients improving scalability, demonstrated by numerical experiments.

Page 1

Download Results (CSV)