Corn-leaf-disease-data

This project shares a subset of the dataset used in the paper “IRG-ResNet: Distillation Model for Corn Disease Recognition”. The dataset subset is curated from a larger collection of corn disease images and is intended for experimental validation in corn disease recognition tasks. The dataset includes multiple representative corn disease categories. All images were collected from real field environments, covering diverse illumination conditions, viewing angles, and disease progression stages. Prior to model training and evaluation, the images were uniformly cleaned and preprocessed to ensure data quality and experimental reproducibility. This dataset subset is provided for research and educational purposes only. It is intended to support studies on lightweight deep learning models, knowledge distillation, and intelligent agricultural disease recognition, and to facilitate fair comparison and reproducibility of related methods. Usage: The dataset subset follows the experimental settings described in the original paper and can be used for image classification or object detection tasks. Details regarding data splitting, training strategies, and evaluation metrics are provided in the paper. If you use this dataset in your research, please cite: IRG-ResNet: Distillation Model for Corn Disease Recognition