Plant Disease Classification Using Convolutional Neural Networks for Precision Farming

This paper has shown a best CNN-based approach to multi-classes plant disease classification with the use of the PlantVillage dataset. The quantitative analysis was conducted to conclude that this model was good in classifying plants according to different criteria like accuracy, precision, recall, and F1 score to prove its usefulness in automated diseasedness detection in agriculture. This discussion also made it clear that deep learning algorithms can be used to facilitate precision farming by reducing the use of laboratory analysis. Future research work would focus on adaptation to field photographs and mobile-based platforms.

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