| Autor: |
Adam, Gh., Buša, J., Hnatič, M., Goncharov, Pavel, Uzhinskiy, Alexander, Ososkov, Gennady, Nechaevskiy, Andrey, Zudikhina, Julia |
| Předmět: |
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| Zdroj: |
EPJ Web of Conferences; 1/10/2020, Vol. 226, p1-4, 4p |
| Abstrakt: |
Crop losses are a major threat to the wellbeing of rural families, to the economy and governments, and to food security worldwide. The goal of our research is to develop a multi-functional platform to help the farming community to tilt against plant diseases. In our previous works, we reported about the creation of a special database of healthy and diseased plants' leaves consisting of five sets of grapes images and proposed a special classification model based on a deep siamese network followed by k-nearest neighbors (KNN) classifier. Then we extended our database to five sets of images for grape, corn, and wheat – 611 images in total. Since after this extension the classification accuracy decreased to 86 %, we propose in this paper a novel architecture with a deep siamese network as feature extractor and a single-layer perceptron as a classifier that results in a significant gain of accuracy, up to 96 %. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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