Artificial Winnowing Scene Classification Dataset

The current agricultural industry faces challenges of low efficiency in crop identification and monitoring. Traditional manual monitoring methods are not only time-consuming but also prone to errors, failing to meet the needs of modern agriculture. Existing solutions often rely on low-quality image data, leading to low classification accuracy. To address these issues, this dataset aims to provide high-quality winnowing scene images to support automated crop identification and monitoring tasks. Data collection is carried out using drones in various farmland environments to ensure coverage of multiple growth states and weather conditions. Each image undergoes multiple rounds of annotation and expert review to ensure consistency and accuracy of labeling. Data is stored in JPG format, organized by image ID for quick access and processing.