16 citations · 16 across the 2 of their papers we have counts for
5 papers
Detector-Free Weakly Supervised Grounding by Separation
Assaf Arbelle, Sivan Doveh, Amit Alfassy +14
Nowadays, there is an abundance of data involving images and surrounding free-form text weakly corresponding to those images. Weakly Supervised phrase-Grounding (WSG) deals with th…
DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation
Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv
We present the DeepHist - a novel Deep Learning framework for augmenting a network by histogram layers and demonstrate its strength by addressing image-to-image translation problem…
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…
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…
Microscopy Cell Segmentation via Convolutional LSTM Networks
Assaf Arbelle, Tammy Riklin Raviv
Live cell microscopy sequences exhibit complex spatial structures and complicated temporal behaviour, making their analysis a challenging task. Considering cell segmentation proble…