UGDA-Net raises Dice coefficient by 9.3% over baseline on a 432-image plant seedling dataset by combining uncertainty-guided attention, entropy-weighted loss, and deep supervision.
Attention-based multi-kernelized and boundary-aware network for image semantic segmentation.Neurocomputing, 597:127988, 2024
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Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation
UGDA-Net raises Dice coefficient by 9.3% over baseline on a 432-image plant seedling dataset by combining uncertainty-guided attention, entropy-weighted loss, and deep supervision.