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filtering approach and a pointcloud matching algorithm. The filtering approach should utilise camera-based classifications, from a sperate module, in the pointcloud data to distinguish different object
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unappealing or suboptimal coverage results. In this thesis, you will first analyze the variety of expected environments and the specific requirements placed on the algorithm. From this, you will evaluate
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quantification. Your task in detail: Design a data pipeline to extract and preprocess activity-relevant features from monitored building power consumption data Develop a classification algorithm (e.g
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<span lang="en">University of Freiburg</span> | Freiburg im Breisgau, Baden-Württemberg | Germany | about 8 hours ago
The Chair of Ecosystem Physiology (https://uni-freiburg.de/enr-ecophys/) in the Faculty of Environment
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buildings Development of strategies for distributed localization and orientation (e.g. sensor fusion, RTLS integration) Implementation of a prototype for coordinating multiple agents/robots in a
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<span lang="en">TUD Dresden University of Technology</span> | Dresden, Sachsen | Germany | 2 days ago
:
- compiler frameworks (LLVM, MLIR)
- embedded software development
- computer and accelerator architectures
- parallel and distributed computing
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experience in algorithm development Enthusiasm for mobile robotics Excellent German or English language skills What we offer Cutting-edge technology in mobile outdoor robotics Hands-on work with our
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pipeline. Therefore, you will investigate different types of predictions like intent prediction, reachability approaches or Bayesian filtering and develop a robust prediction algorithm. These dynamic
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Helmholtz Association of German Research Centres | Geesthacht, Schleswig-Holstein | Germany | 2 months ago
are often sparse and unevenly distributed. In the AEON-UP project, we develop a transferable AI system for high-resolution urban air quality prediction across European cities and combine: - physics
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challenge current notions of transparency, auditability, and certification. While Model Cards and Data Cards are emerging as best practices, they are insufficient for complex, distributed AI services