Demo Data from VLDB 2026 / reviewers in the wild / expert
Kazuma Shinkai
dblp:324/6350
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021
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 · 77% Robot manipulation · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
depth image analysis |
0.6 | 1 | 2022 | Depth Distribution Split Labeling for Rubble Recognition of Crushing Machine · ICRA 2022 |
Methods — techniques the papers use, named apart from their topics
hydraulic cylinder pressure sensing · 0.6depth distribution split labeling · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Depth Distribution Split Labeling for Rubble Recognition of Crushing MachineabstractThis paper describes rubble recognition using a depth image sensor and an automatic rubble crushing system using a construction machine for automatic rubble crushing at a building demolition site. Depth Distribution Split Labeling (DDSL) is proposed to recognize irregularly shaped rubble using depth images and to identify the largest rubble in the workspace. In DDSL, we focused on the fact that the depth of the contact area of adjacent rubble is lower, and labeling by dividing the depth makes it possible to identify the rubble. The automatic rubble crushing system enables to avoid excessive pushing and to grasp objects based on the cylinder driving force calculated from the hydraulic cylinder internal pressure of the construction machine. Through evaluation experiments simulating the crushing environment, it was confirmed that the proposed system can identify and automatically crush rubble. Takahiro Ikeda, Satoshi Ueki, Kazuma Shinkai, Hironao Yamada |
ICRA | 3 |