Optimized Matrix Feature Analysis – Convolutional Neural Network (OMFA-CNN) Model for Potato Leaf Diseases Detection System

One of the most often grown crops is potato. As a main food, potatoes are prioritised for cultivation worldwide. Because such rich source vitamins and minerals, we can create robust system food security. However, number illnesses delay growth agriculture harm potato output. Consequently, early disease identification offer better answer effective crop production. In this research work aim to classify detect leave (PL) diseases using OMFA-CNN deep learning model. An optimized matrix feature analysis-CNN model PL detection implemented. first phase, PLs features extracted from images K-means clustering image segmentation method. At last new proposed CNN virus, bacterial PLs, The dataset consists 2351 gathered in real-time Kaggle (PlantVillage) dataset. implemented attained 99.3 % precision 99 recall on detection. method also compared with MASK RCNN,SVM other models significantly high recall.