AEMS-Net, a U-Net variant with KAN convolutions, attention, and brightness adaptation, reconstructs mitochondrial and microtubule images from one fluorescence image and reports large gains over vanilla U-Net.
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Interpretable deep learning illuminates multiple structures fluorescence imaging: a path toward trustworthy artificial intelligence in microscopy
AEMS-Net, a U-Net variant with KAN convolutions, attention, and brightness adaptation, reconstructs mitochondrial and microtubule images from one fluorescence image and reports large gains over vanilla U-Net.