Lightweight neural networks for event-based vision

Stage M2/Ingénieur (+thèse) Stage de fin d’études : Réseaux de neurones légers pour la vision basée événementsMaster Internship: Lightweight neural networks for event-based vision Description en français Notre laboratoire est spécialisé dans le contrôle de robots mobiles, tels que des voitures et des drones intelligents. Nous nous focalisons sur les…

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Tissue characterization through speckle in ultrasound images with deep learning

Stage M2 Location: CREATIS Laboratory, Villeurbanne, France Subject: Histopathology is currently the gold-standard technique for tissue characterization. Nevertheless, it is a local, invasive, time-consuming and expensive method. Tissue characterization through imaging would enable a global analysis of the organ without invasiveness or additional cost. Ultrasound images include speckle, which is…

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Generalization of Graph Neural Networks on Large Graphs

Stage M2 (+thèse) Graph Neural Network (GNN) [3] are state-of-the-art deep models that can perform a wide range ofGraph Machine Learning (Graph ML) task on graph data, with many applications in chemistry, biology, or recommender systems, to name a few. Most GNN architectures are built by stacking layers of functions…

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Évaluation physique et émotionnelle des exercices de rééducation via apprentissage profond

Stage M2 / Ingénieur Dans le domaine des soins de santé, les exercices de rééducation physique sont essentiels pour la récupération post-opératoire et la gestion des troubles musculo-squelettiques [1,2]. Toutefois, la réussite de ces exercices ne dépend pas seulement de leur exécution correcte. L’expérience émotionnelle et physique des patients joue…

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Comparaison d’images texturées par Carte de Dissimilarités Locales – Application aux images médicales

Stage M2 Contexte Le CReSTIC a développé un outil dédié à la comparaison d’images numériques, permettant la détection, la localisation et la quantification des écarts entre deux images : la Carte des Dissimilarités Locales (CDL) [1]. En l’état, la CDL est capable de mesurer avec efficacité des dissimilarités locales entre…

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Quantifying Multiple Sclerosis Progression with Deep Learning

Multiple Sclerosis (MS) is the most widely prevalent chronic disabling disease affecting the central nervous system in young adults. The diagnosis of MS remains largely guided by clinical expertise, as opposed to laboratory findings. Investigations via magnetic resonance imaging (MRI) help by providing diagnostic support and deeper insights. The use…

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Prompt Engineering for Visual Language Foundation Models

Stage M2 The internship will take place in the Laboratory of Medical Information Processing (LaTIM- INSERM UMR 1101). It will be conducted within the framework of the LabCOM ADMIRE, a research unit created by Evolucare Technologies and LaTIM (https://anr.fr/Projet-ANR-19-LCV2-0005). Context The joint collaboration between LaTIM and Evolucare Technologies resulted in…

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Modeling the evolution of Age-related Macular Degeneration using AI

Required background: Ongoing M2 or ING3 in Image Processing, Artificial Intelligence, Machine Learning, Deep Learning Place of internship: ISEP campus at Issy-Les-Moulineaux (Subway “Corentin Celton” on line 12). Occasional meetings at Paris 15-20 Hospital (Paris, 75012). Internship beginning: February 2024 Internship duration: 5 to 6 months Salary: 440€/month Application Contact…

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