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K-PIE: using K-means algorithm for Percentage Infection symptoms Estimation

Vanessa Bueno-Sancho; Pilar Corredor-Moreno; Ngonidzashe Kangara; Diane G.O. Saunders


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  <dc:creator>Vanessa Bueno-Sancho</dc:creator>
  <dc:creator>Pilar Corredor-Moreno</dc:creator>
  <dc:creator>Ngonidzashe Kangara</dc:creator>
  <dc:creator>Diane G.O. Saunders</dc:creator>
  <dc:date>2019-12-19</dc:date>
  <dc:description>The K-means algorithm is one of the most effective clustering methods that has been widely used in plant disease detection. Herein, we developed a script termed K-PIE (K-means algorithm for Percentage Infection symptoms Estimation) that utilises the k-means algorithm to analyse images of both yellow and stem rust infected wheat leaves to estimate the percentage of disease symptoms based on colour analysis.</dc:description>
  <dc:identifier>https://zenodo.org/record/3584148</dc:identifier>
  <dc:identifier>10.5281/zenodo.3584148</dc:identifier>
  <dc:identifier>oai:zenodo.org:3584148</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/715638/</dc:relation>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/674964/</dc:relation>
  <dc:relation>info:eu-repo/grantAgreement/RCUK/BBSRC/BB%2FM011216%2F1/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3584147</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Wheat rust</dc:subject>
  <dc:subject>plant pathology</dc:subject>
  <dc:subject>image analysis</dc:subject>
  <dc:subject>K-mean algorithm</dc:subject>
  <dc:title>K-PIE: using K-means algorithm for Percentage Infection symptoms Estimation</dc:title>
  <dc:type>info:eu-repo/semantics/technicalDocumentation</dc:type>
  <dc:type>publication-technicalnote</dc:type>
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