Abstract
Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as
food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple
food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming
practices. In the United States, for example, the Midwest is known as the "Corn Belt" due to its extensive corn production. Corn
crops can be grown using a variety of methods, including conventional tillage, no-till farming, and the use of genetically modified
crops. Due to its importance, there is a need for discovering the corn diseases and treating them. The aim of this study is to propose
a deep learning model for the classification of corn leaf diseases based on Convolutional Neural Network. A model for classifying
maize diseases was developed using a dataset for classifying Corn diseases that contains 4 classes of disease. The dataset was
collected from Keggel website. The proposed model was trained, validated, and tested. The F1-score (99.83%), Recall (99.83%),
precision (99.83%), Accuracy (99.83%).