Plant Pest Recognition Dataset

The current agricultural industry is facing crop yield reduction due to pest infestations, especially under the influence of climate change where both the types and numbers of pests are increasing. Existing pest recognition methods often rely on human experience, which is inefficient and prone to errors. Therefore, there is an urgent need to utilize AI technology for automated recognition. The aim of this dataset is to provide researchers and developers with high-quality pest image data to improve the accuracy and efficiency of pest recognition. Data collection is done using high-resolution cameras across different farmland environments to ensure diversity and representativeness. Data annotation undergoes multiple rounds of review and expert validation to ensure accuracy and consistency. The data is stored in JPG format, organized in such a way that each image folder contains the corresponding annotation information, facilitating subsequent processing and analysis. The dataset construction process includes sample selection, photographing, annotation, review, and storage.