The DEBS 2019 Grand Challenge

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • Oleh Bodunov - (Autor:in)
  • Vincenzo Gulisano - (Autor:in)
  • Hannaneh Najdataei - (Autor:in)
  • Zbigniew Jerzak - (Autor:in)
  • André Martin - , Professur für Systems Engineering (SE) (Autor:in)
  • Pavel Smirnov - (Autor:in)
  • Martin Strohbach - (Autor:in)
  • Holger Ziekow - (Autor:in)

Abstract

The ACM DEBS 2019 Grand Challenge is the ninth in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2019 Grand Challenge is on the application of machine learning to LiDAR data. The goal of the challenge is to perform classification of objects found in urban environments and sensed in several 3D scenes by the LiDAR. The applications of LIDAR and object detection go well beyond autonomous vehicles and are suitable for use in agriculture, waterway maintenance and flood prevention, and construction. This paper describes the specifics of the data streams provided in the challenge as well as the benchmarking platform that supports the testing of corresponding solutions.

Details

OriginalspracheEnglisch
TitelDEBS '19: Proceedings of the 13th ACM International Conference on Distributed and Event-based Systems
Herausgeber (Verlag)Association for Computing Machinery (ACM), New York
Seiten205–208
Band2019
ISBN (elektronisch)978-1-4503-6794-3
PublikationsstatusVeröffentlicht - 2019
Peer-Review-StatusJa

Publikationsreihe

ReiheDEBS: Distributed Event-based Systems

Externe IDs

Scopus 85074402378

Schlagworte

Forschungsprofillinien der TU Dresden

DFG-Fachsystematik nach Fachkollegium

Schlagwörter

  • LiDAR, point cloud, streaming, event processing, event processing, streaming, LiDAR, point cloud

Bibliotheksschlagworte