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, a unique opportunity opens up for you: Explore the potential of machine learning and computer vision to revolutionize autonomous flight systems. In close collaboration with leading industry partners
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, are all essential advancements to enable a wider and more secure deployment of the technology. Most biometric systems are based on image analyses. Therefore, exciting challenges in the computer vision
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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computational tools to evaluate models of biological and artificial vision, as part of the DFG-funded Collaborative Research Center (CRC) “Robust Vision” at the University of Tübingen. This is a unique
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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Familiarity with computer vision techniques; experience with segmentation, tracking, or video analysis is a plus Basic understanding of materials microstructures, grain growth, and electron microscopy would be
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Photonic Networks and Systems department is conducting research on the next
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to the success of the whole institution. At the Faculty of Computer Science, Institute of Computer Engineering, the Chair of Compiler Construction offers a project position, subject to the availability