Technical note Open Access

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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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3584148", 
  "title": "K-PIE: using K-means algorithm for Percentage Infection symptoms Estimation", 
  "issued": {
    "date-parts": [
      [
        2019, 
        12, 
        19
      ]
    ]
  }, 
  "abstract": "<p>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.</p>", 
  "author": [
    {
      "family": "Vanessa Bueno-Sancho"
    }, 
    {
      "family": "Pilar Corredor-Moreno"
    }, 
    {
      "family": "Ngonidzashe Kangara"
    }, 
    {
      "family": "Diane G.O. Saunders"
    }
  ], 
  "version": "Version 1.0", 
  "type": "article", 
  "id": "3584148"
}
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