Alternate identifier:
( 773196217178836992) Mobilithek
Related identifier:
-
Contributors:
(Project Member)
(Project Member)
(Supervisor)
Friedle, Dirk [Civil Engineering Department, Karlsruhe]
Title:
Synset Signset Germany
Additional titles:
-
Description:
(Abstract) The synthetic Synset Signset Germany dataset addresses the task of traffic sign recognition for the country of Germany. In this, it combines the advantages of data-driven and analytical modeling: GAN-based texture generation enables data-driven dirt and wear artifacts to create unique and realistic ...
Keywords:
KAMO
traffic sign recognition
machine learning
Related information:
-
Language:
English
Production year:
Subject areas:
Computer Science
Resource type:
Dataset
Data source:
-
Software used:
Resource production
Software:
OCTAS - 0.1
Alternative software:
-
Data processing:
-
Publication year:
Funding:
Federal Ministry for Economic Affairs and Climate Action - (AVEAS)(19A32056E)
Fraunhofer Society - (ML4Safety)(PREPARE 40-02702)
Name Storage Metadata Upload Action
Status:
Published
Uploaded by:
jens.ziehn@iosb.fraunhofer.de
Created on:
Archiving date:
2025-10-01
Archive size:
17.1 GB
Archive creator:
56687fad80f114d240c0f8d45eb78498
Archive checksum:
373656812a1d57a899f8289c340544b8 (MD5)
Embargo period:
-

Geolocation

  • GERMANY