Deep Learning-Based Web Application for Real-Time Apple Leaf Disease Detection and Classification
Satish Kumar, Rakesh Kumar, Meenu Gupta, Ahmed J. Obaid
Abstract
Agriculture is the most significant industry in the economy of India. Various kinds of diseases affect the leaves of plants and influence the productivity of crops. Apple farmers are also constantly facing challenges in boosting their yield and protecting apple trees from diseases. The prevalence of diseases and pests significantly hampers apple production, leading to substantial financial losses for the industry each year. Farmers may not have expertise in leaf disease prediction. Detecting Apple Leaf Diseases (ALD) swiftly and accurately is crucial for effectively handling and curbing these issues within orchards. Specifically, advancements in computer vision methods utilizing Deep Learning (DL) have opened up avenues for identifying and understanding these diseases at an early stage directly on the leaves. Web application based on the DL model is proposed to address this issue, which can predict Healthy and Alternaria, Leaf Spot, Marssonina Blotch, and Powdery mildew disease of the affected leaf.