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Field
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Student assistant (m/f/d)-Multi-Modal Sensor Fusion, Object Detection in Clutter and Object Tracking
. The focus here is robust multi-camera fusion, accurate object detection in cluttered scenes (bulk goods), and multi-modal tracking that combines camera data with tactile feedback. Using deep learning, multi
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of several doctoral positions within the Marie Sklodowskaja Curie Action Doctoral Network EXPLORA: Perception of materials, objects and spaces through active EXPLORAtion: https://explora-network.github.io/web
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recognition systems and for automated, robot-assisted object reconstruction and quality inspection. What you will do During your internship, you will work on a research project involving fault detection
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classification algorithms need to be extended with the capability to detect out-of-distribution environments and to autonomously infer their traversability. In this thesis, you will design a semantic
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recognition systems and for automated, robot-assisted object reconstruction and quality inspection. What you will do During your internship, you will work on a research project involving fault detection
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Stud. assistant (m/f/d) - Obj. Detection in clutter and Obj. Tracking in robotic hand (in Heilbronn)
. The focus here is robust multi-camera fusion, accurate object detection in cluttered scenes (bulk goods), and multi-modal tracking that combines camera data with tactile feedback. Using deep learning, multi
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faults that affect their performance and energy consumption. Effective and timely fault detection is essential to maintain optimal operation and reduce downtime. In this context, the application
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Image-based acquisition of the current state of arbitrary object geometries has
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Through regular scanning missions and assignments, 3D scans of diverse objects
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