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In summary, the weed image dataset is a comprehensive collection of images and metadata designed to support research in the field of weed management. The diverse and large dataset provides a wealth of data for computer vision algorithms to learn from, helping to improve the accuracy and efficiency of automatic weed detection in agricultural fields.
An Agricultural Image Repository for the United States
Semi-Automatic Labeling
A major component of NAIR and the semi-automatic labeling approach is the development of plant segments, or cutouts, that can be used to develop temporary datasets of synthetic images for training annotation assistant detection and segmentation models. Synthetic data along with weak image labels is used to iteratively refine whole image labels.
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