Name
Title | ||
|---|---|---|
DDE process: A requirements engineering approach for machine learning in automated driving |
Abstract | ||
|---|---|---|
Machine learning (ML) is key to achieve complex automation like in self-driving cars: implementation of implicit requirements and faster time-to-market are just two promises. Despite technological advances, research questions remain open about improving the level of trust and quality (quality in terms of ISO 25010) that can be placed on such ML-based systems. Their quality depends on the quality o... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/RE51729.2021.00031 | 2021 IEEE 29th International Requirements Engineering Conference (RE) |
Keywords | DocType | ISSN |
data-driven engineering,autonomous driving,automated driving,machine learning,data requirements,V-model,process | Conference | 2332-6441 |
ISBN | Citations | PageRank |
978-1-6654-2856-9 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran Zhang | 1 | 33 | 13.46 |
| Andreas Albrecht | 2 | 0 | 0.34 |
| Jonathan Kausch | 3 | 0 | 0.34 |
| Henrik J. Putzer | 4 | 0 | 0.34 |
| Thomas Geipel | 5 | 0 | 0.34 |
| Prashanth Halady | 6 | 0 | 0.34 |