eMiL
Embedded Machine Learning
(Third Party Funds Single)
Title of the overall project:
Project start: 01/10/2021
Acronym: eMiL
Funders: Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie (StMWi) (seit 2018)
Abstract
The aim of this project is to design and build a machine learning system that is networked across different levels, from sensors to the cloud, and optimised as a whole. The advantages of such a system can be optimally demonstrated by using the latest radar sensor technology. For this purpose, novel ML signal processing algorithms for person recognition are developed in order to realise high-resolution environment detection for autonomous transport vehicles. The focus for the system should be on modularity, reusability, flexibility and scalability, as well as the closest possible interlocking of the subcomponents.
Publications
2024
Automated Radar Data Labeling using MoveNet for Human Gesture Recognition (Conference contribution, accepted)
BibTeX: Download , , , :
Gesture Recognition to Control a Moving Robot With FMCW Radar (Conference contribution, accepted)
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2023
Automated Radar Data Labeling through Computer Vision
Wamicon (Melbourne, FL 32903, 17/04/2023 - 18/04/2023)
DOI: 10.1109/WAMICON57636.2023.10124886
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