A dataset for A Statistically Validated Stacking Ensemble of CNNs and Vision Transformer for Robust Maize Disease Classification

This dataset provides the necessary resources to further explore a statistically validated stacking ensemble model combining Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) for maize disease classification. The dataset is designed to support research for disease recognition, enabling improved automated disease detection in maize crops. The dataset includes Maize Dataset Manifest excell data, which is A structured rows of Excel sheet that provides the dataset's contents, including metadata for each image file and important information about dataset organization. It contains also Generated Raw Data for Maize Leaf Disease in PDF format, which is a detailed report generated from Python containing raw data on maize leaf disease used for model training and validation. Therefore, this row data assists researchers in developing deep learning models for scalable maize disease detection.