activity
20102023
most citedExploiting Statistical Dependencies in Sparse Representations for Signal Recovery

129 citations · 231 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2023

SDAT: Sub-Dataset Alternation Training for Improved Image Demosaicing

Yuval Becker, Raz Z. Nossek, Tomer Peleg

Image demosaicing is an important step in the image processing pipeline for digital cameras. In data centric approaches, such as deep learning, the distribution of the dataset used…

cs.CV2023

Do More With What You Have: Transferring Depth-Scale from Labeled to Unlabeled Domains

Alexandra Dana, Nadav Carmel, Amit Shomer +2

Transferring the absolute depth prediction capabilities of an estimator to a new domain is a task with significant real-world applications. This task is specifically challenging wh…

cs.CV2021

You Better Look Twice: a new perspective for designing accurate detectors with reduced computations

Alexandra Dana, Maor Shutman, Yotam Perlitz +3

General object detectors use powerful backbones that uniformly extract features from images for enabling detection of a vast amount of object types. However, utilization of such ba…

cs.IT2013★ 99 cited

Fundamental performance limits for ideal decoders in high-dimensional linear inverse problems

Anthony Bourrier, Mike E. Davies, Tomer Peleg +2

This paper focuses on characterizing the fundamental performance limits that can be expected from an ideal decoder given a general model, ie, a general subset of "simple" vectors o…

cs.IT2012★ 3 cited

Performance Guarantees of the Thresholding Algorithm for the Co-Sparse Analysis Model

Tomer Peleg, Michael Elad

The co-sparse analysis model for signals assumes that the signal of interest can be multiplied by an analysis dictionary Ω, leading to a sparse outcome. This model stands as an int…

cs.IT2010★ 129 cited

Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery

Tomer Peleg, Yonina C. Eldar, Michael Elad

Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in…