Search Results for author: Daniel Freedman

Found 17 papers, 5 papers with code

SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits

1 code implementation11 Dec 2021 Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, Ady Arie

In addition, our method can be readily applied for controlling other degrees of freedom of light in the SPDC process, such as the spectral and temporal properties, and may even be used in condensed-matter systems having a similar interaction Hamiltonian.

It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems

no code implementations NeurIPS 2021 Regev Cohen, Yochai Blau, Daniel Freedman, Ehud Rivlin

In this work, we introduce image denoisers derived as the gradients of smooth scalar-valued deep neural networks, acting as potentials.

Denoising

Deep Unfolding with Normalizing Flow Priors for Inverse Problems

no code implementations6 Jul 2021 Xinyi Wei, Hans van Gorp, Lizeth Gonzalez Carabarin, Daniel Freedman, Yonina C. Eldar, Ruud J. G. van Sloun

Many application domains, spanning from computational photography to medical imaging, require recovery of high-fidelity images from noisy, incomplete or partial/compressed measurements.

Deblurring Image Denoising

Inverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystals

no code implementations20 Feb 2021 Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, Ady Arie

We introduce a systematic approach for designing 3D nonlinear photonic crystals and pump beams for generating desired quantum correlations between structured photon-pairs.

Learning an optimal PSF-pair for ultra-dense 3D localization microscopy

no code implementations29 Sep 2020 Elias Nehme, Boris Ferdman, Lucien E. Weiss, Tal Naor, Daniel Freedman, Tomer Michaeli, Yoav Shechtman

A long-standing challenge in multiple-particle-tracking is the accurate and precise 3D localization of individual particles at close proximity.

Detecting Deficient Coverage in Colonoscopies

no code implementations23 Jan 2020 Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin

Our coverage algorithm is the first such algorithm to be evaluated in a large-scale way; while our depth estimation technique is the first calibration-free unsupervised method applied to colonoscopies.

Depth Estimation

Detecting muscle activation using ultrasound speed of sound inversion with deep learning

no code implementations20 Oct 2019 Micha Feigin, Manuel Zwecker, Daniel Freedman, Brian W. Anthony

Functional muscle imaging is essential for diagnostics of a multitude of musculoskeletal afflictions such as degenerative muscle diseases, muscle injuries, muscle atrophy, and neurological related issues such as spasticity.

Localization with Limited Annotation for Chest X-rays

no code implementations19 Sep 2019 Eyal Rozenberg, Daniel Freedman, Alex Bronstein

We present such a technique for localization with limited annotation, in which the number of images with bounding boxes can be a small fraction of the total dataset (e. g. less than 1%); all other images only possess a whole image label and no bounding box.

DeepSTORM3D: dense three dimensional localization microscopy and point spread function design by deep learning

1 code implementation21 Jun 2019 Elias Nehme, Daniel Freedman, Racheli Gordon, Boris Ferdman, Lucien E. Weiss, Onit Alalouf, Reut Orange, Tomer Michaeli, Yoav Shechtman

Localization microscopy is an imaging technique in which the positions of individual nanoscale point emitters (e. g. fluorescent molecules) are determined at high precision from their images.

Super-Resolution

Unsupervised Single Image Dehazing Using Dark Channel Prior Loss

1 code implementation6 Dec 2018 Alona Golts, Daniel Freedman, Michael Elad

Instead of feeding the network with synthetic data, we solely use real-world outdoor images and tune the network's parameters by directly minimizing the DCP.

Image Dehazing Single Image Dehazing

A Deep Learning Framework for Single-Sided Sound Speed Inversion in Medical Ultrasound

no code implementations30 Sep 2018 Micha Feigin, Daniel Freedman, Brian W. Anthony

Conclusion: Sound speed inversion on channel data has significant potential, made possible in real time with deep learning technologies.

Deep-Energy: Unsupervised Training of Deep Neural Networks

1 code implementation31 May 2018 Alona Golts, Daniel Freedman, Michael Elad

The success of deep learning has been due, in no small part, to the availability of large annotated datasets.

Image Dehazing Image Matting +1

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

1 code implementation ICLR 2019 Or Litany, Daniel Freedman

We present SOSELETO (SOurce SELEction for Target Optimization), a new method for exploiting a source dataset to solve a classification problem on a target dataset.

Bilevel Optimization Classification +2

ASIST: Automatic Semantically Invariant Scene Transformation

no code implementations4 Dec 2015 Or Litany, Tal Remez, Daniel Freedman, Lior Shapira, Alex Bronstein, Ran Gal

We present ASIST, a technique for transforming point clouds by replacing objects with their semantically equivalent counterparts.

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