Demo Data from SIGIR 2026 / reviewers in the wild / expert
Sami Atiya
dblp:03/2129
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1993
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, 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.
| Artificial intelligence
1 paper |
Robot navigation and mapping · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
landmark matching |
0.0 | 1 | 1993 | Real-time vision-based robot localization · IEEE Trans. Robotics Autom. 1993 |
Robotics › Robot navigation and mapping
localization |
0.0 | 1 | 1993 | Real-time vision-based robot localization · IEEE Trans. Robotics Autom. 1993 |
Robotics › Robot navigation and mapping › localization
vision-based localization |
0.0 | 1 | 1993 | Real-time vision-based robot localization · IEEE Trans. Robotics Autom. 1993 |
Methods — techniques the papers use, named apart from their topics
geometric tolerance · 0.0error bounding · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1993 | Real-time vision-based robot localizationabstractThis paper describes an algorithm for determining robot location from visual landmarks. This algorithm determines both the correspondence between observed landmarks (in this case vertical edges in the environment) and a stored map, and computes the location of the robot using those correspondences. The primary advantages of this algorithm are its use of a single geometric tolerance to describe observation error, its ability to recognize ambiguous sets of correspondences, its ability to compute bounds on the error in localization, and fast execution. The algorithm has been implemented and tested on a mobile robot system. In several hundred trials it has never failed, and computes location accurate to within a centimeter in less than 0.5 s.> Sami Atiya, Gregory D. Hager |
IEEE Trans. Robotics Autom. | 1 |