Improving the Robustness of Unexpected Obstacle Detection Models in Autonomous Driving Systems /Amélioration de la Robustesse des Modèles de Détection d’Obstacles inattendus dans les Systèmes de Conduite Autonome

Stage M2 Contact: isetitra@utc.fr. Autonomous driving systems heavily depend on effective environmental perception, particularly in the area of object detection. Although YOLO (You Only Look Once) models [1][2][3] have established themselves as a standard for real-time object detection due to their balance between accuracy and speed, they show limitations when…

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Unrolled proximal algorithms for estimating the reproduction number of Covid-19 pandemic

Stage M Master internship of 4 to 6 months in 2025 located at Laboratoire des Sciences du Numérique de Nantes (LS2N). Supervision and contact: Barbara Pascal (barbara.pascal@cnrs.fr) and Sébastien Bourguignon (sebastien.bourguignon@ec-nantes.fr). Application: Send a CV, master grades, references and motivations to B. Pascal and S. Bourguignon.   Epidemics, striking heavily…

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Unbalanced Optimal Transport-based regularization – Application to inverse problems in epidemiology

Master internship of 4 to 6 months in 2025 located at Laboratoire des Sciences du Numérique de Nantes (LS2N). Supervision and contact: Barbara Pascal (barbara.pascal@cnrs.fr) and Jérôme Idier (jerome.idier@ls2n.fr). Application: Send a CV, master grades, references and motivations to B. Pascal and J. Idier. Epidemic monitoring is a burning issue…

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Leveraging matrix-variate distributions for ultrasound imaging

Stage M2 / Ingénieur Annonce complète : https://www.creatis.insa-lyon.fr/site/fr/node/47662 Leveraging matrix-variate distributions for ultrasound imaging Context Cardiovascular diseases cause more than half of all deaths across Europe and around one-third globally. It is thus crucial to develop diagnostic tools to improve how patients with these diseases are cared for. This internship…

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3D image reconstruction dedicated to tomographic diffractive microscopy for unlabeled samples

Subject title: 3D image reconstruction dedicated to tomographic diffractive microscopy for unlabeled samples.Host laboratory: Laboratoire Hubert Curien (LaHC), 18 Rue Pr B. Lauras, 42000 SAINT-´ETIENNE.Supervisor and contact: Fabien Momey Casella (fabien.momey@univ-st-etienne.fr).Keywords: 3D (tomographic) image reconstruction, numerical simulation, scientific programming with Matlab®,tomographic diffractive microscopy, biomedical applications.Duration: 6 months.Starting date: february/march 2025.Salary:…

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Extraction de caractéristiques par apprentissage profond pour le spike sorting

Stage de Master M2 au CRAN, Nancy (03-08/2024): apprentissage profond pour la classification de potentiels d’action neuronaux. Les potentiels d’action, ou spikes en anglais, constituent la base de la communication neuronale, permettant la transmission d’informations au sein des réseaux cérébraux. Ces activités électriques, générées par des neurones individuels, peuvent être…

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Fusion d’images spectrales de spectrométrie de masse (MSI) et de microscopie à fluorescence (IF)

Nous recherchons un(e) étudiant(e) en M2 pour un stage au sein de notre équipe de recherche de l’IPBS Toulouse, CNRS UMR 5089, spécialisée dans l’étude du microenvironnement des tumeurs mammaires. Nous travaillons principalement sur des techniques d’imagerie par spectrométrie de masse (MSI) pour l’étude des petites molécules et des lipides…

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Epilepsies caused by genetic mutations: signal processing and computational modeling

Post-doc or Research Engineer position offer (ref: RHU2024-MICRO) Epilepsies caused by genetic mutations: signal processing and computational modeling Context. Developmental and epileptic encephalopathies (DEEs) are a group of severe rare diseases where the combined effect of seizures, most often drug resistant, and the non-seizures consequences of the disease etiology, often…

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Generative Models for Garment Mesh

Geometric deep learning has emerged in the fields of computer graphics and computer vision, enabling deep learning models to operate on geometric data such as graphs, meshes, manifolds, and point clouds. Some notable models in this area include Graph Convolutional Networks (GCNs), PointNet, Geodesic Neural Networks (GNNs), and specialized architectures…

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