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sensors, such as the Underwater Vision Profiler or the ZooScan, as well as an increase number of software packages to process and control the quality of the data generated by the instruments, sort images
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) — to join our team. You will be directly involved in developing and optimizing ion beam processes to improve device performance in MRAM and magnetic sensor applications. Beyond R&D, we are looking for a
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topological textures. A wide range of applied functionalities could be considered: terahertz sources, unconventional computing and AI, security components, telecommunications, sensors, memories etc.
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initiatives, the French Mineral Resources Inventory, and European research projects on new quantum gravimetric sensors. In these projects, as well as in future initiatives, you will be involved from
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a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, becoming a key component for managing smart cities. Except for a few applications, DAS data are typically
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. SequoIA focuses on urban monitoring using Distributed Acoustic Sensing, a technique that repurposes existing telecom optical fibers as continuous, high-resolution seismo-acoustic sensors. This passive and
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detection, to cite a few. As telecom fibers are ubiquitous in urban environments, DAS appears as a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, and a key component
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complicates both learning and inference processes. Another challenge is that dynamic structured data are generated by a variety of sensors and infrastructures that continuously produce, disseminate, and store
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, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
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to perceive their environment because this sensor can produce precise depth measurement at a high density. LiDARs measurements are generally sparse, mainly geometric and lacks semantic information. Therefore