M. Fayz-al-asad

JPNet: A multi-layered fusion deep learning architecture for the detection and classification of pests in jute crops

Detecting and classifying insect pests is a critical challenge in agricultural pest management, as infestations can reduce crop yield and quality. This study introduces JPNet, a convolutional neural network (CNN) architecture that uses multi-layer feature fusion to detect and classify insect pests affecting jute crops....