Multi-Crop Field Crop Recognition Dataset

The current agricultural industry faces challenges such as inaccurate crop recognition, low monitoring efficiency, and high labor costs. Existing crop recognition solutions perform poorly in multi-crop environments, making it difficult for farmers to obtain accurate information in crop management decisions. This dataset aims to help agricultural technology companies and research institutions by providing high-quality field crop recognition data to enhance the accuracy and efficiency of crop monitoring. The dataset includes 20,000 images covering different growth stages of crops and supports object detection tasks. Data collection uses high-resolution cameras under various lighting and climate conditions to ensure diversity and representativeness of samples. Quality control measures include multiple rounds of annotation and expert review to ensure the accuracy and consistency of data annotations. The data is stored in JPG format, with metadata records corresponding to each image.