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What is Recurrent U-Net for Efficient Segmentation about?

This paper introduces a novel recurrent U-Net architecture for resource-constrained segmentation tasks. The recurrent U-Net architecture preserves the compactness of the original U-Net while substantially increasing its performance. With only 0.3 million parameters, the recurrent U-Net outperforms state-of-the-art models on several benchmarks, including hand segmentation, retina vessel segmentation, and road segmentation. The recurrent U-Net is much smaller than models using ResNet101 as the backbone, makin

Author

leon.sergio.tf

Language

EN