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TGV methodology MATLAB implementation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APR36443" target="_blank" >RIV/00216305:26210/22:PR36443 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0141938222001044#mmc1" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0141938222001044#mmc1</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    TGV methodology MATLAB implementation

  • Original language description

    n implementation of TGV methodology published in TGV searches for an optimal setting of a computer vision system or of its sub-system. Within the system/sub-system must be implemented a weighted means grayscale conversion method. This implementation of TGV is based on one-stage grid-search algorithm supervised by a computer vision expert. The expert assesses settings proposed by the grid-searc method using WECIA graphs. One WECIA graph displays dependence of the system performance on setting of the grayscale conversion weights for one specific setting of the remaining adjustable parameters of the system/sub-system. The performance of the system/sub-system can be evaluated using one or more objective functions where only one of these function is used as a primary objective function, i.e. the grid-search algorihm uses this function for the selection of the optimal parameter setting. The expert can use all the objective functions while assessing a setting proposed by the grid-search algorithm, i.e. nJ WECIA graph are displeyed for one assesed setting where nJ is the number of the objective functions.

  • Czech name

  • Czech description

Classification

  • Type

    R - Software

  • 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/LTC18053" target="_blank" >LTC18053: Advanced Methods of Nature-Inspired Optimisation and HPC Implementation for the Real-Life Applications</a><br>

  • Continuities

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

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Internal product ID

    TGV

  • Technical parameters

    freeware

  • Economical parameters

    Not applicable

  • Owner IČO

    00216305

  • Owner name

    Vysoké učení technické v Brně