Potato Plant Leaf Disease Detection using optimized CNN and Transfer Learning

Abstract

The plant disease is a significant concern in the agriculture field. Many diseases destroy the crop badly. Optimized Convolutional neural network (CNN) model having seven convolutional layer with weight pruning is used for detecting disease on potato leaves. Further transfer learning is used to compare the results of the proposed model. Plant Village dataset which contains potato disease-Early blight and late blight is used. Both the diseases are fungaldiseases. Used transfer learning models are Resnet50, VGG16 and VGG19.

Plant phenotyping relevance

ジャガイモ葉の病害状態を画像から検出するCNN手法を開発・比較しており、植物病害フェノタイピングが中心である。

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