CA-Cut, a crop-aligned masking augmentation, reduces semantic keypoint prediction error in under-canopy cornfield navigation by up to 36.9 percent over a non-masking baseline.
Bbox- cut: A targeted data augmentation technique for enhancing wheat head detection under occlusions,
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CA-Cut: Crop-Aligned Cutout for Data Augmentation to Learn More Robust Under-Canopy Navigation
CA-Cut, a crop-aligned masking augmentation, reduces semantic keypoint prediction error in under-canopy cornfield navigation by up to 36.9 percent over a non-masking baseline.