Survey on Deep Learning Technique on Maize Leaves Infected by Fall Armyworms
摘要
One of the most commercially successful cereal crops farmed worldwide is maize (Zea mays L.), which is a common staple food in many developing nations. Each year, significant yield losses occur due to infestation of fall armyworms. The goal of this work is to develop a deep learning-based model that is trained on images of healthy and fall armyworm-infested maize leaves from a dataset using Convolutional Neural Network (CNN) architecture and enhance the accuracy using Ensemble learning. So, classification of leaves on the basis of infestation of fall armyworms, that is healthy or infected, can lead to early detection of infestation in leaves and steps can be taken as per requirement.