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Computer Science

D-Index
45
Citations
14757
World Ranking
7015
National Ranking
114

Overview

Nir Sochen is affiliated with Tel Aviv University in Israel. Their research spans multiple disciplines including Engineering, Computer Science, and Medicine, with a significant focus on subfields such as Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Aerospace Engineering, Media Technology, and Industrial and Manufacturing Engineering.

The scientist has contributed extensively to topics including Advanced Neuroimaging Techniques and Applications, Infrared Target Detection Methodologies, Image and Signal Denoising Methods, MRI in cancer diagnosis, Advanced MRI Techniques and Applications, Advanced Vision and Imaging, and Mathematical Analysis and Transform Methods.

Recent notable papers authored or co-authored by Nir Sochen include:

  • Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification, 2021, Human Brain Mapping
  • Strong Solutions for PDE-Based Tomography by Unsupervised Learning, 2021, SIAM Journal on Imaging Sciences
  • Cross-site harmonization of multi-shell diffusion MRI measures based on rotational invariant spherical harmonics (RISH), 2022, NeuroImage
  • Deep Learning Solution of the Eigenvalue Problem for Differential Operators, 2023, Neural Computation
  • Computational end-to-end and super-resolution methods to improve thermal infrared remote sensing for agriculture, 2020, Precision Agriculture

Frequent co-authors in Nir Sochen's publications include:

  • Iftach Klapp
  • Navot Oz
  • Ofer Pasternak
  • David Mendlovic
  • Yogesh Rathi

Publication venues where Nir Sochen has frequently contributed are diverse with multiple articles appearing in:

  • arXiv (Cornell University)
  • Optics Express
  • Human Brain Mapping
  • SIAM Journal on Imaging Sciences
  • NeuroImage

Best Publications

  • An Algorithm for Total Variation Minimization and Applications

    Mila Nikolova

  • Free water elimination and mapping from diffusion MRI.

    Ofer Pasternak;Nir Sochen;Yaniv Gur;Nathan Intrator

  • A general framework for low level vision

    N. Sochen;R. Kimmel;R. Malladi

  • Image enhancement and denoising by complex diffusion processes

    G. Gilboa;N. Sochen;Y.Y. Zeevi

  • Forward-and-backward diffusion processes for adaptive image enhancement and denoising

    G. Gilboa;N. Sochen;Y.Y. Zeevi

  • A Fast Spectral Method for Active 3D Shape Reconstruction

    Jia Li;Alfred O. Hero

  • Images as Embedded Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images

    R. Kimmel;R. Malladi;N. Sochen

  • Integrated active contours for texture segmentation

    Chen Sagiv;N.A. Sochen;Y.Y. Zeevi

  • Variational denoising of partly textured images by spatially varying constraints

    G. Gilboa;N. Sochen;Y.Y. Zeevi

  • Towards recognition-based variational segmentation using shape priors and dynamic labeling

    Daniel Cremers;Nir Sochen;Christoph Schnörr

  • From High Energy Physics to Low Level Vision

    Ron Kimmel;Nir A. Sochen;Ravi Malladi

  • Image Deblurring in the Presence of Impulsive Noise

    Leah Bar;Nahum Kiryati;Nir Sochen

  • Regularized Shock Filters and Complex Diffusion

    Guy Gilboa;Nir A. Sochen;Yehoshua Y. Zeevi

  • Estimation of optimal PDE-based denoising in the SNR sense

    G. Gilboa;N. Sochen;Y.Y. Zeevi

  • Deblurring of Color Images Corrupted by Impulsive Noise

    L. Bar;A. Brook;N. Sochen;N. Kiryati

  • A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation

    Daniel Cremers;Nir Sochen;Christoph Schnörr

  • Image deblurring in the presence of salt-and-pepper noise

    Leah Bar;Nir Sochen;Nahum Kiryati

  • Orientation Diffusion or How to Comb a Porcupine

    Ron Kimmel;Nir Sochen

  • Diffusions and Confusions in Signal and Image Processing

    N. Sochen;R. Kimmel;A. M. Bruckstein

  • Shape-from-Shading Under Perspective Projection

    Ariel Tankus;Nir Sochen;Yehezkel Yeshurun

  • Image Sharpening by Flows Based on Triple Well Potentials

    Guy Gilboa;Nir Sochen;Yehoshua Y. Zeevi

Frequent Co-Authors

Ron Kimmel
Ron Kimmel Technion – Israel Institute of Technology
Yehoshua Y. Zeevi
Yehoshua Y. Zeevi Technion – Israel Institute of Technology
Nahum Kiryati
Nahum Kiryati Tel Aviv University
Ofer Pasternak
Ofer Pasternak Brigham and Women's Hospital
Hayit Greenspan
Hayit Greenspan Tel Aviv University
Alexander M. Bronstein
Alexander M. Bronstein Technion – Israel Institute of Technology
Michael M. Bronstein
Michael M. Bronstein University of Oxford
Joachim Weickert
Joachim Weickert Saarland University
Baba C. Vemuri
Baba C. Vemuri University of Florida
Rachid Deriche
Rachid Deriche French Institute for Research in Computer Science and Automation - INRIA

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