All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

A New Approach to Vector Field Interpolation, Classification and Robust Critical Points Detection Using Radial Basis Functions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43953674" target="_blank" >RIV/49777513:23520/19:43953674 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-91192-2_12" target="_blank" >http://dx.doi.org/10.1007/978-3-319-91192-2_12</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-91192-2_12" target="_blank" >10.1007/978-3-319-91192-2_12</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A New Approach to Vector Field Interpolation, Classification and Robust Critical Points Detection Using Radial Basis Functions

  • Original language description

    Visualization of vector fields plays an important role in many applications. Vector fields can be described by differential equations. For classification null points, i.e. points where derivation is zero, are used. However, if vector field data are given in a discrete form, e.g. by data obtained by simulation or a measurement, finding of critical points is difficult due to huge amount of data to be processed and differential form usually used. This contribution describes a new approach for vector field null points detection and evaluation, which enables data compression and easier fundamental behavior visualization. The approach is based on implicit form representation of vector fields.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless methods for large scattered spatio-temporal vector data visualization</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Cybernetics and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing

  • ISBN

    978-3-319-91191-5

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    109-115

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    online

  • Event date

    Apr 25, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article