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IN VIVO FISH DIET DISCRIMINATION USING SELECTED HYPERSPECTRAL IMAGE CLASSIFICATION METHODS

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F18%3A43899358" target="_blank" >RIV/60076658:12520/18:43899358 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/8747074" target="_blank" >https://ieeexplore.ieee.org/document/8747074</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    IN VIVO FISH DIET DISCRIMINATION USING SELECTED HYPERSPECTRAL IMAGE CLASSIFICATION METHODS

  • Original language description

    The main aim of this study was to evaluate the performance of different supervised classification methods to discriminate live fish based on their diet received during cultivation using hyperspectral imagery system. 160 rainbow trout were fed either a commercial based diet or completely plant-based diet. Hyperspectral images of the live fish acquired in the spectral region of 394-1090 nm. Spectra were extracted from the region of interest and pre-processed using Savitzky-Golay smoothing algorithm to remove noise. Afterward, three classifiers including support vector machine, random forest and k-nearest neighbors were used. According to the criteria of correct classification rate and kappa coefficient, the support vector machine with linear kernel was achieved the best performance for classifying live fish due to their diet.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2018 9TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS)

  • ISBN

    978-1-72811-581-8

  • ISSN

    2158-6268

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    5

  • Publisher name

    IEEE

  • Place of publication

    NEW YORK

  • Event location

    Amsterdam

  • Event date

    Sep 23, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000482659100036