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20182021
most citedDynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

cs.LG20211 cited

Dynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities

Lizeth Gonzalez-Carabarin, Iris A. M. Huijben, Bastiaan S. Veeling +2

Unstructured neural network pruning algorithms have achieved impressive compression rates. However, the resulting - typically irregular - sparse matrices hamper efficient hardware…

eess.IV2019

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging

Iris A. M. Huijben, Bastiaan S. Veeling, Kees Janse +2

Limitations on bandwidth and power consumption impose strict bounds on data rates of diagnostic imaging systems. Consequently, the design of suitable (i.e. task- and data-aware) co…

eess.SP2019

Deep learning in ultrasound imaging

Ruud JG van Sloun, Regev Cohen, Yonina C Eldar

We consider deep learning strategies in ultrasound systems, from the front-end to advanced applications. Our goal is to provide the reader with a broad understanding of the possibl…

cs.LG2018

Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

Oren Solomon, Regev Cohen, Yi Zhang +5

Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It…

physics.med-ph2018

Exploiting flow dynamics for super-resolution in contrast-enhanced ultrasound

Oren Solomon, Ruud J. G. van Sloun, Hessel Wijkstra +2

Ultrasound localization microscopy offers new radiation-free diagnostic tools for vascular imaging deep within the tissue. Sequential localization of echoes returned from inert mic…