What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Optics
- Computer vision
Yoav Y. Schechner mainly investigates Artificial intelligence, Computer vision, Optics, Image formation and Polarizer.
His work in the fields of Pixel and Rendering overlaps with other areas such as Microphone and Audio signal processing.
His Computer vision study frequently draws parallels with other fields, such as Attenuation.
He combines subjects such as Image processing and Image detection with his study of Optics.
Yoav Y. Schechner interconnects Distance transform and Color correction in the investigation of issues within Image formation.
His Polarizer research includes themes of Diffuse sky radiation, Haze and Optical polarization.
His most cited work include:
- Instant dehazing of images using polarization (586 citations)
- Blind Haze Separation (409 citations)
- Polarization-based vision through haze (393 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Computer vision, Optics, Pixel and Scattering.
His research in Artificial intelligence intersects with topics in Focus and Attenuation.
Image formation, Rendering, High dynamic range, Image restoration and Iterative reconstruction are among the areas of Computer vision where he concentrates his study.
The study incorporates disciplines such as Image processing and Haze in addition to Optics.
His research integrates issues of Visibility, Depth map and Remote sensing, Radiance in his study of Pixel.
His Light scattering study in the realm of Scattering connects with subjects such as Computed tomography.
He most often published in these fields:
- Artificial intelligence (51.28%)
- Computer vision (46.15%)
- Optics (27.56%)
What were the highlights of his more recent work (between 2017-2021)?
- Tomography (10.26%)
- Remote sensing (14.10%)
- Artificial intelligence (51.28%)
In recent papers he was focusing on the following fields of study:
Yoav Y. Schechner focuses on Tomography, Remote sensing, Artificial intelligence, Scattering and Computer vision.
His study on Tomography is covered under Optics.
His study in Remote sensing is interdisciplinary in nature, drawing from both Pixel, Radiative transfer, Computational photography and Polarimetry.
His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Microscopy.
The various areas that Yoav Y. Schechner examines in his Scattering study include Tomographic reconstruction, Voxel, Atmospheric radiative transfer codes and Attenuation coefficient.
Many of his research projects under Computer vision are closely connected to Thesaurus with Thesaurus, tying the diverse disciplines of science together.
Between 2017 and 2021, his most popular works were:
- The unprecedented 2017–2018 stratospheric smoke event: decay phase and aerosol properties observed with the EARLINET (21 citations)
- A Correlated Multi-Pixel Inversion Approach for Aerosol Remote Sensing (13 citations)
- Dynamic heterodyne interferometry (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Optics
- Computer vision
The scientist’s investigation covers issues in Tomography, Pixel, Remote sensing, Optics and Polarization.
His work is dedicated to discovering how Tomography, Scattering are connected with Tomographic reconstruction, Inverse problem, Photon, Imaging phantom and Rayleigh scattering and other disciplines.
His Pixel study incorporates themes from Inversion, Aerosol remote sensing and Rendering.
Yoav Y. Schechner has researched Remote sensing in several fields, including Ground truth, Computational photography, Light field and Temporal resolution.
His research links Phase image with Optics.
His Polarization research incorporates themes from Radiative transfer and Medical imaging.
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