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Scientific Vision Days
- /en/about-the-ait/center/center-for-vision-automation-control/translate-to-english-messen-events/scientific-vision-days
technologies in the field of machine vision. Together with the Industrial Vision Days, the Scientific Vision Days lecture series forms the lecture forum of the VISION trade fair and offers a platform for [...] Scientific Vision Days The AIT Austrian Institute of Technology lecture series Scientific Excellence on Stage at VISION trade fair, Stuttgart AIT Booth | Hall 8 C50 The SCIENTIFIC VISION DAYS are the [...] 1500 characters) Scientific Vision Days Program 2024 This year's topics include 3D vision, high-speed imaging, inline computational imaging, deep learning, and testing of vision systems. We have already received
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Sustainable & flexible Manufacturing Systems
- /en/solutions/sustainable-flexible-manufacturing-systems
+43 664 88256031 martin.niederer(at)ait.ac.at To the Center for Vision, Automation & Control To the Research Groups High-Performance Vision Systems Assistive & Autonomous Systems Complex Dynamical Systems [...] values are derived from laboratory experiments and then prescribed for the process as recipes. Our vision combines the latest hybrid material models to capture specific material properties with mathematical
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Perception, Localisation & Mapping
- /en/research-topics/perception-localisation-mapping
+43 664 8157877 manfred.gruber(at)ait.ac.at To the Center for Vision, Automation & Control To the Research Groups High-Performance Vision Systems Assistive & Autonomous System Complex Dynamical Systems [...] systems). Machine & Deep Learning In addition to the "traditional" sensor data analysis such as computer vision, machine learning is essential for a proper perception of the surroundings. In recent years, we have
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AI & MACHINE LEARNING
- /en/research-topics/ai-machine-learning
664 88904331 maximilian.liebetreu(at)ait.ac.at To the Center for Vision, Automation & Control To the Research Groups High-Performance Vision Systems Assistive & Autonomous Systems Complex Dynamical Systems [...] self-supervised learning forces models to learn embeddings on labelled data. Successful examples include vision transformers and graph neural networks (geometric cue learning, deep geometric learning, knowledge
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