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Field
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on the development of first-time-right design tools for multi-optics imaging systems, to be implemented in harsh condition vision applications. In modern perception, navigation and quality inspection applications
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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applied to computer vision and image analysis. Analytical thinking and problem-structuring skills, including the ability to abstract complex systems, identify core research challenges, and develop
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of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB photography domain
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Image processing and computer vision Experimental data analysis and uncertainty quantification Piezoelectric actuation, acoustic systems or electronic driver development Eligibility and Project
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the development of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB
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with a group of ~3–4 people, as part of a microscopy team of ~25 people, as well as interactions with collaborators at the Institut de la Vision (Paris). École Polytechnique is located in the Paris
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computer vision, deep learning, and logical reconstruction techniques. The research investigates how multimodal imaging modalities - including scanning electron microscopy (SEM), photon emission microscopy
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming