An Optimized Hyper Parameter Tuned Convolution Neural Frame for Potato Leaves Disease Prediction

Image processing is an exciting concept in several digital applications for identifying features precisely. Hence, this technology chiefly utilized agriculture to predict the disease affection plat and leaves. However, complex image has reduced exactness rate of classification segmentation. In present work, potato leaves are normal, images considered. a novel Ant Lion-based Hyper-Parameter tuned Convolution Neural Approach (ALHTCNA) been designed with required parameters maximize score. Initially, preprocessing function was activated obtain error-free data. Consequently, data moved frame, that feature extraction, segmentation, process functioned. The considered types work Early-Blight (EB) Late-Blight (LB). If tested did not contain these features, it healthy Moreover, planned design implemented python platform, metrics validated compared other schemes observed finest segmentation specification