Synthetic Crop-Weed Image Generation and its Impact on Model Generalization
PositiveArtificial Intelligence
This article discusses a new method for generating synthetic crop-weed images to aid in training deep learning models for agricultural robots. By using Blender, the authors create annotated datasets that can help bridge the gap between simulated and real images, making it easier and more cost-effective to develop precise semantic segmentation for weeding robots.
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