Plant Leaf Disease Detection and Classification using Optimized CNN Model

Our economy depends on productivity in agriculture. The quantity and quality of the yield is greatly affected by various hazardous diseases. Early-stage detection plant disease will be very helpful to prevent severe damage. Automatic systems detect changes plants monitoring abnormal symptoms its growth more beneficial for farmers. This paper presents a system automatic prediction classification leaf survey diseases techniques that can used are also discussed. proposed define cropped image through processing feature extraction algorithms. Enhanced CNN model designed applied about 20,600 images collected as dataset. Optimization done enhance accuracy show improvement true positive samples classification. shows 93.18% three different species with twelve