Name: Julian Kunze
Type: User
Company: Leibniz University Hannover
Bio: Researcher at LUH,
research on autonomous UAVs for deployment in disaster scenarios,
M.Sc. Robotics, Cognition, Intelligence from TUM
Location: Hannover, Germany
Blog: https://www.linkedin.com/in/juliankunze/
Julian Kunze's Projects
Code for CVPR 2022 paper '3D Moments from Near-Duplicate Photos'
Intelligent Decision Support System for House Price Prediction
kernelized large-scale metric learning from equivalence constraints
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
megastep helps you build 1-million FPS reinforcement learning environments on a single GPU
Collection of utilities for working with Menge configuration and output files
Course Project on Large-Scale ML
Integration of YOLO Object Detection and SORT Tracking algorithm applied to JAAD dataset
This code can be used on a mobile robot for avoiding obstacles. This code was originally written for use with a Summit XL mobile robot from Robotnik using laser readings as the means for determining obstacles. However it can be configured to be used for any mobile robot using either laser and/or sonar readings. It is based on the use of a potential
Optimal Reciprocal Collision Avoidance, Python bindings
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.