Plant Disease Detection Using Image Processing and Deep Learning

Plant diseases are a major problem in agriculture because they reduce crop production and cause heavy financial losses for farmers around the world.Detecting plant diseases at an early stage is very important for maintaining crop quality and improving food security.In recent years, technologies such as image processing and deep learning have become effective solutions for automatic plant disease detection.This paper provides an overview of different plant disease detection systems based on image processing and deep learning methods.It explains popular techniques such as Convolutional Neural Networks (CNN), Support Vector Machines (SVM), Random Forest, and transfer learning models like ResNet and VGG16.The study also discusses important steps including image preprocessing, feature extraction, disease classification, and performance evaluation.In addition, it highlights the major challenges faced in plant disease detection and explores possible future improvements in this field.