Demo Data from EDBT 2026 / reviewers in the wild / expert
Taeko Gotoh
dblp:35/5015
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
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.
| Artificial intelligence
1 paper |
3D vision · 56% Probabilistic and Bayesian machine learning · 28% Legged, aerial and field robots · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision › range sensing
depth sensing |
0.0 | 1 | 2003 | Evaluation of shadow range finder: SRF for planetary surface exploration · ICRA 2003 |
Computer vision › 3D vision › depth estimation
range estimation |
0.0 | 1 | 2003 | Evaluation of shadow range finder: SRF for planetary surface exploration · ICRA 2003 |
Machine learning › Probabilistic and Bayesian machine learning
sampling |
0.0 | 1 | 2003 | Evaluation of shadow range finder: SRF for planetary surface exploration · ICRA 2003 |
Robotics › Legged, aerial and field robots › field robotics
planetary rover |
0.0 | 1 | 2003 | Evaluation of shadow range finder: SRF for planetary surface exploration · ICRA 2003 |
Robotics › Robot manipulation › tactile sensing
surface exploration |
0.0 | 1 | 2003 | Evaluation of shadow range finder: SRF for planetary surface exploration · ICRA 2003 |
Methods — techniques the papers use, named apart from their topics
single-camera measurement · 0.0image thresholding · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Evaluation of shadow range finder: SRF for planetary surface explorationabstractTo gather a rock, it is necessary how to get information of the surface around a sample. Usually, a surface information is brought by a special sensor such as Laser Range Finder and Stereo Camera. These sensors, however, needs more weight and power consumption and are used for only one function such as the surface measurement. And furthermore, there are some difficulties to use those sensors in some case. In this research, we propose Shadow Range Finder: SRF, which can make good use of a shadow for the measurement of a surface information under the direct sunlight. Shadow is strong for above mentioned problem, and would be recognized in the case of a halation. The measurement by SRF uses a single camera, which should be installed on a manipulator for a sampling, and a link of a manipulator, which produce its shadow. The principle of SRF is same as Laser Range Finder, and a shadow is used for scanning slit instead of a laser. In this paper, experimental results of actual objects is shown, and we discusses about accuracy of measurement data. Finally, we evaluate image thresholding method by the consideration of theoretical value at a circular light source. Yasuharu Kunii, Taeko Gotoh |
ICRA | 2 |