1.2k citations · 2.3k across the 64 of their papers we have counts for
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Multimodal Unrolled Robust PCA for Background Foreground Separation
Spencer Markowitz, Corey Snyder, Yonina C. Eldar +1
Background foreground separation (BFS) is a popular computer vision problem where dynamic foreground objects are separated from the static background of a scene. Typically, this is…
Point of Care Image Analysis for COVID-19
Daniel Yaron, Daphna Keidar, Elisha Goldstein +22
Early detection of COVID-19 is key in containing the pandemic. Disease detection and evaluation based on imaging is fast and cheap and therefore plays an important role in COVID-19…
COVID-19 Classification of X-ray Images Using Deep Neural Networks
Elisha Goldstein, Daphna Keidar, Daniel Yaron +24
In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in the diagnosis and monitoring of patients with COVID-19.…
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
Vishal Monga, Yuelong Li, Yonina C. Eldar
Deep neural networks provide unprecedented performance gains in many real world problems in signal and image processing. Despite these gains, future development and practical deplo…
Deep Algorithm Unrolling for Blind Image Deblurring
Yuelong Li, Mohammad Tofighi, Junyi Geng +2
Blind image deblurring remains a topic of enduring interest. Learning based approaches, especially those that employ neural networks have emerged to complement traditional model ba…
HYDRA: Hybrid Deep Magnetic Resonance Fingerprinting
Pingfan Song, Yonina C. Eldar, Gal Mazor +1
Purpose: Magnetic resonance fingerprinting (MRF) methods typically rely on dictio-nary matching to map the temporal MRF signals to quantitative tissue parameters. Such approaches s…