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]. Au-delà de la turbulence, les systèmes actifs denses peuvent également présenter des oscillations spontanées auto-entretenues, comme déjà observées dans les foules humaines denses et les tissus
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machine learning for cybersecurity, current systems remain largely based on pattern recognition and struggle to incorporate contextual reasoning, temporal dependencies, and relationships between entities
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project at the forefront of microscopy and bioimage analysis (https://www.msca-agile.eu/ ) and contribute to OMERO integration and optimization of Biom3d, a cutting-edge deep-learning framework for 3D image
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for managing smart cities. The team has gained substantial experience in machine learning for road traffic monitoring. They are now keen to thoroughly explore the additional opportunities presented by
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) and a global ocean model (NEMO). The selected candidate will contribute to the ANR-AIAI project (https://anr-aiai.github.io ). Scientific Context The melting of Antarctic ice shelves by the ocean is a
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validate adaptive mechanisms for LoRaWAN based on machine learning techniques, targeting improved reliability and energy efficiency in mobile scenarios. To achieve this, it is necessary to go beyond
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technologies, such as low-power long-range (LoRa) and high-throughput, low-latency technologies (5G). In the context of machine learning, communications play a central role in data sharing and in the decision
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et d'assurer la stabilité des performances dans le temps. Cette thèse s'inscrit dans le cadre de l'apprentissage continu, un domaine émergent du machine learning, qui vise à concevoir des modèles
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of deep learning in many disciplines, particularly computer vision and image processing. Consequently, coding architectures based on deep learning and end-to-end optimization have been proposed [Ding 2021