Crop diseases and pests are important factors determining the yield and quality of plants. Crop diseases identification and pest’s suggestion can be carried out by means of digital image processing. In recent years, deep learning has made breakthroughs in the field of digital image processing, far superior to traditional methods. How to use deep learning technology to study Crop diseases and pests suggestion has become a research issue of great concern to researchers. In this project we evaluate three crops 1) Lettuce 2) Hibiscus Sabdarifa 3) Brassica oleracea to detect disease and suggest pesticides. This review provides a definition of crop diseases detection problem, puts forward a comparison with traditional plant diseases and pests detection methods. According to the difference of network structure, this study outlines the research on crop diseases based on deep learning in recent years. In this project we use CNN (Convolutional neural network) model to detect plants disease and also it suggests the pesticide regarding the disease.

KEYWORDS: Convolutional Neural Network, Deep Learning, Hygiene Crops.