Demo Data from SIGIR 2026 / reviewers in the wild / expert
Myungjin Cho
dblp:122/1658
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-2896-770XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Computational photography and imaging · 88% Visualization and visual analytics · 12% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational photography and imaging
3d imaging |
0.1 | 1 | 2011 | Three-Dimensional Optical Sensing and Visualization Using Integral Imaging · Proc. IEEE 2011 |
Computational photography and imaging › light field imaging
integral imaging |
0.1 | 1 | 2011 | Three-Dimensional Optical Sensing and Visualization Using Integral Imaging · Proc. IEEE 2011 |
Visualization and visual analytics
3d visualization |
0.0 | 1 | 2011 | Three-Dimensional Optical Sensing and Visualization Using Integral Imaging · Proc. IEEE 2011 |
Computational photography and imaging
multi-perspective imaging |
0.0 | 1 | 2011 | Three-Dimensional Optical Sensing and Visualization Using Integral Imaging · Proc. IEEE 2011 |
Methods — techniques the papers use, named apart from their topics
range estimation · 0.1computational reconstruction · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Amplitude based keyless optical encryption system using deep neural network
Kotaro Inoue, Myungjin Cho |
J. Vis. Commun. Image Represent. | 2 |
| 2011 | Three-Dimensional Optical Sensing and Visualization Using Integral ImagingabstractThree-dimensional (3-D) optical image sensing and visualization technologies have been researched extensively for different applications in fields as diverse as entertainment, medical sciences, robotics, manufacturing, and defense. In many instances, the capabilities of 3-D imaging and display systems have revolutionized the progress of these disciplines, enabling new detection/display abilities that would not have been otherwise possible. As one of the promising methods in the area of 3-D sensing and display, integral imaging offers passive and relatively inexpensive way to capture 3-D information and to visualize it optically or computationally. The integral imaging technique belongs to the broader class of multiview imaging techniques and is based on a century old principle which has only been resurrected in the past decade owing to advancement of optoelectronic image sensors as well as the exponential increase in computing power. In this paper, historic and physical foundations of integral imaging are overviewed; different optical pickup and display schemes are discussed and system parameters and performance metrics are described. In addition, computational methods for reconstruction and range estimation are presented and several applications including 3-D underwater imaging, near infra red passive sensing, imaging in photon-starved environments, and 3-D optical microscopy are discussed among others. Myungjin Cho, Mohammad Mehdi DaneshPanah, Inkyu Moon, Bahram Javidi |
Proc. IEEE | 1 |