Crop Diseases and Pest Detection using Deep Learning and Image Processing Techniques

Abstract

Crop pests and diseases play a significant role in yield reduction and quality. Controlling and preventing pests and crop diseases has therefore become a priority. If disease is detected at an early stage, this can increase crop production and provide benefit to farmers. Manual detection of these diseases and pests can be very tedious and time consuming for farmers, especially if they have large farms. We plan to model a crop disease and pest diagnostic system using image processing and deep learning techniques. Crop disease and pest detection can be done using deep learning and image recognition techniques on leaves and other areas of the crop.

Plant phenotyping relevance

葉などの画像から作物病害を深層学習・画像処理で診断する方法の開発が中心で、植物の病徴という状態を直接推定しているため。

Code and data availability

The paper's own analysis relies on the open-source PlantVillage leaf image dataset, which is a public, paper-specific phenotyping input asset. However, no authors' code, trained model, or repository URL is provided in the supplied text, so only the dataset qualifies, and even it lacks an explicit authors' deposit URL;