Demo Data from EDBT 2026 / reviewers in the wild / expert
Lorenz A. Schmitt
dblp:74/1926
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorHuman-computer interaction and ubiquitous 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Processor architecture and microarchitecture · 50% Parallel and multicore computing · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel architecture
massively parallel processor |
0.0 | 1 | 1988 | The AIS-5000 Parallel Processor · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Processor architecture and microarchitecture
SIMD |
0.0 | 1 | 1988 | The AIS-5000 Parallel Processor · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Methods — techniques the papers use, named apart from their topics
virtual two-dimensional model · 0.0performance benchmarking · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | The AIS-5000 Parallel ProcessorabstractThe AIS-5000 is a commercially available massively parallel processor which was designed to operate in an industrial environment. It has fine-grained parallelism with up to 1024 processing elements arranged in a single-instruction multiple-data (SIMD) architecture. The processing elements are arranged in a one-dimensional chain that, for computer vision applications, can be as wide as the image itself. The overall architecture of the system is described. Various components of the system are discussed, including details of the processing elements, data I/O (input/output) pathways and parallel memory organization. A virtual two-dimensional model for programming image-based algorithms for the system is also presented. Performance benchmarks are given for certain simple and complex functions.> Lorenz A. Schmitt, Stephen S. Wilson |
IEEE Trans. Pattern Anal. Mach. Intell. | 1 |
| 1986 | A Robot Vision System Based on Two-Dimensional Object-Oriented ModelsabstractMachine vision offers manufacturing industries a more cost-effective means of developing and implementing robotic applications. How using a vision sensor can increase the flexibility and usefulness of robots in specific manufacturing applicatons is described, provided that specific features of the robot-vision application development environment are present. These features include an object model representation that incorporates both statistical and relational information, a robot-vision interface that accommodates the flow of data and control between the vision sensor and the robot controller, and an integrated user progranunng environment that allows the development of object-oriented robotic applications. A system is described that incorporates these features and some requirements for future development of robot vision are given. Lorenz A. Schmitt, William A. Gruver, Assad Ansari |
IEEE Trans. Syst. Man Cybern. | 1 |