16 citations · 63 across the 23 of their papers we have counts for
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cs.CV2019
Hue-Net: Intensity-based Image-to-Image Translation with Differentiable Histogram Loss Functions
Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv
We present the Hue-Net - a novel Deep Learning framework for Intensity-based Image-to-Image Translation. The key idea is a new technique termed network augmentation which allows a…
cs.CV2019★ 2 cited
QANet -- Quality Assurance Network for Image Segmentation
Assaf Arbelle, Eliav Elul, Tammy Riklin Raviv
We introduce a novel Deep Learning framework, which quantitatively estimates image segmentation quality without the need for human inspection or labeling. We refer to this method a…