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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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and 4D reconstruction in combination with Gaussian splatting Synthesis of new, photorealistic images with object manipulation for dataset generation using state-of-the-art view synthesis methods, based
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between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods. As part of
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distributed energy storage like stationary batteries and hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven
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they interact with. By representing items through rich multimodal embeddings (from images and text) and modeling user behavior as a sequence, the system can dynamically adapt to new content and users without
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architecture exploration, hardware/software co-design and operating/runtime systems. Typical application domains are e.g. signal-/image processing, artificial intelligence and machine learning. Tasks: research
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With its focus on future-relevant key technologies and the utilization of results in economy and industry, the Fraunhofer Society plays a central role in the innovation process. As a guide and
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of a prototype software module that automatically generates feedback in the defined format from the selected metrics and tests. Quantitative and qualitative evaluation of the feedback process by
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. The processes that take place in the layer of the Earth’s surface between the upper side of the bedrock and the atmospheric boundary layer – which encompasses near-surface groundwater, soil, and vegetation – play
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power, energy, space) to develop systems that reliably capture and process input data such as images and speech and provide comprehensible feedback. This topic opens a wide range of possible applications