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This dataset was created to support this research by providing a diverse and large collection of labeled images that represent different types of weeds, cover crops, and crops, grown in different settings and growing conditions. A semi-automatic approach that uses photogrammetry, classical digital image processing, and deep learning has been used to generate multiple type of labels, capturing information about the plants present in the image, and making them suitable across various machine learning tasks. Here, you will find a comprehensive overview of the dataset, including its contents, annotation process, metadata, characteristics, and availability.
Makeup
NAIR is made-up of 3 broad plant datasets:
Weeds (WIR)
Cover crops (CCIR)
Cash crops (CIR)