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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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Learning" team has AI expertise and we have a high-performance IT infrastructure available. For our "Computer Vision and Machine Learning" team, we are looking for a student assistant as soon as possible
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age-related macular degeneration (AMD). AMD is the most common cause of vision loss in elderly affecting about 300 million people by 2040. Currently, there is no effective treatment for the majority
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in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi
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this knowledge gap and establish improved GHG models accounting for soil invertebrates. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental
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Technische Universität Berlin, Electrical Engineering and Computer Science (Faculty IV) Position ID: Technische Universität Berlin -Electrical Engineering and Computer Science (Faculty IV) -PHD
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR. • Know-how/Interest in designing user studies. • Excellent communication skills and a collaborative spirit to work with