Plant Leaf Diseases Prediction Using Convolutional Neural Network (CNN)

Leaf diseases can cause severe damage to crops and plants, reducing overall output and quality. Early diagnosis of these diseases can help in avoiding their spread and minimizing their impact. In this study, we offer a unique approach for detecting leaf diseases using machine-learning algorithms. To effectively distinguish healthy and damaged leaves, we use image processing techniques and deep learning algorithms. We test our suggested method on a dataset of plant leaves and reach an optimum accuracy. Our method can be applied to a variety of plant species and can assist farmers in diagnosing and managing leaf diseases. In the past and present, farmers have traditionally relied on their naked eye to detect crop diseases, which often forces them to make difficult decisions about which fertilizers to use. This process requires extensive knowledge of different disease types and a great deal of experience to ensure accurate disease detection. Unfortunately, some diseases can look almost identical, which often leaves farmers in a state of confusion.