Continental (@continental)
  • Stars
    star
    133
  • Global Org. Rank 50,208 (Top 16 %)
  • Registered over 6 years ago
  • Most used languages
    Python
    53.8 %
    C++
    15.4 %
    Java
    15.4 %
    Ruby
    7.7 %
    C#
    7.7 %
  • Location πŸ‡©πŸ‡ͺ Germany
  • Country Total Rank 8,273
  • Country Ranking
    Ruby
    508
    C#
    1,860
    C++
    1,894
    Python
    2,835
    Java
    3,126

Top repositories

1

megamerge

Multi Repository Pull Request Orchestration
Ruby
34
star
2

image-statistics-matching

Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation
Python
30
star
3

udp_com

Generic UDP communication ROS package
C++
18
star
4

cloud-yourself

A system to manage cloud accounts in large enterprises.
C#
9
star
5

RelaxedLasso

Implementation of Relaxed Lasso Algorithm for Linear Regression.
Python
9
star
6

continental-nodes-for-knime

The Continental Nodes for KNIME Extension provides data processing and reporting capabilities intended for business users of the KNIME Analytics Platform.
Java
9
star
7

hfl_driver

ROS driver for Continental's 3D Flash Lidar
C++
7
star
8

hybrid_learning

Libraries for analysing and using linear concept embeddings of deep neural networks
Python
5
star
9

jenkins_plugin_joblogger

A plugin which writes Jenkins Build information into a CSV formatted log file.
Java
3
star
10

everything-polynomial

A framework for OOD testing across Argoverse 2 Motion and Waymo Open Motion Datasets.
Python
1
star
11

jenkins_log_parser

Create a readable log out of the raw log data from a jenkins job.
Python
1
star
12

kiabsicherung-metric-benchmarking-tool

The Metric Benchmarking Tool (MBT) is an application to perform standard benchmarks using the KI Absicherung (KIA) dataset for 2D object detection. It is meant to allow evaluations of the effectiveness of different methods, by comparing the results calculated by this tool using defined metrics.
Python
1
star
13

kiwissen-bayesian-trajectory-prediction

Framework for integrating prior knowledge into trajectory prediction models for autonomous driving via Bayesian continual learning.
Python
1
star