Search Results for author: Vadim Holodovsky

Found 6 papers, 0 papers with code

Monotonicity Prior for Cloud Tomography

no code implementations ECCV 2020 Tamar Loeub, Aviad Levis, Vadim Holodovsky, Yoav Y. Schechner

An important natural signal of this tendency is the optical extinction coefficient, as a function of altitude in a cloud.

Learned 3D volumetric recovery of clouds and its uncertainty for climate analysis

no code implementations9 Mar 2024 Roi Ronen, Ilan Koren, Aviad Levis, Eshkol Eytan, Vadim Holodovsky, Yoav Y. Schechner

We demonstrate the approach in simulations and on real-world data, and indicate the relevance of 3D recovery and uncertainty to precipitation and renewable energy.

Computed Tomography (CT) Self-Supervised Learning

Advances in 3D scattering tomography of cloud micro-physics

no code implementations18 Mar 2021 Masada Tzabari, Vadim Holodovsky, Omer Shubi, Eitan Eshkol, Yoav Y. Schechner

We introduce new adjustments and advances in space-borne 3D volumetric scattering-tomography of cloud micro-physics.

Retrieval

3DeepCT: Learning Volumetric Scattering Tomography of Clouds

no code implementations ICCV 2021 Yael Sde-Chen, Yoav Y. Schechner, Vadim Holodovsky, Eshkol Eytan

We present 3DeepCT, a deep neural network for computed tomography, which performs 3D reconstruction of scattering volumes from multi-view images.

3D Reconstruction

3D Scattering Tomography by Deep Learning with Architecture Tailored to Cloud Fields

no code implementations10 Dec 2020 Yael Sde-Chen, Yoav Y. Schechner, Vadim Holodovsky, Eshkol Eytan

We present 3DeepCT, a deep neural network for computed tomography, which performs 3D reconstruction of scattering volumes from multi-view images.

3D Reconstruction

In-situ multi-scattering tomography

no code implementations7 Dec 2015 Vadim Holodovsky, Yoav Y. Schechner, Anat Levin, Aviad Levis, Amit Aides

We formulate tomography that handles arbitrary orders of scattering, using a monte-carlo model.

Object

Cannot find the paper you are looking for? You can Submit a new open access paper.