Plant Disease Detection and Classification using Machine Learning Algorithm
Keywords: Deep Learning, InceptionV3 Architecture, Pre-Processing, Res Net.
In this study, we proposed a deep learning approach built on the InceptionV3 Architecture to recognize leaf diseases in a range of plants. Our goal is to identify the plant illness and classify it. The dataset that is being referred to is collected from the renowned online resource Kaggle. There are 70,295 photos of plants in the dataset, including tomatoes, blueberries, cherries, apples, grapes, oranges, pepper bell peppers, potatoes, raspberries, soy beans, strawberries, and corn (maize). The suggested approach may successfully diagnose a variety of diseases and is capable of handling complex situations from a plants' perspective.