By replacing U-Net components with trainable versions of guided and Frangi filters, the authors achieve comparable performance on retinal vessel segmentation with 10x fewer parameters and direct mapping to signal processing tools.
Nature 521(7553), 436 (2015)
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A Divide-and-Conquer Approach towards Understanding Deep Networks
By replacing U-Net components with trainable versions of guided and Frangi filters, the authors achieve comparable performance on retinal vessel segmentation with 10x fewer parameters and direct mapping to signal processing tools.