4 offres stage machine learning trouvées

Joining LINEACT at CESI for a research internship would be a fantastic opportunity to contribute to innovative projects while deepening my skills in a cutting-edge environment Abstract The study explores the development and utilization of digital twins and extended reality tools to enhance remote maintenance procedures, focusing on creating a functional digital twin and developing an interface for device control in extended reality. Keywords : Extended Reality, Digital twin The technological advancements of Industry 4.0 and the human-centric approaches of Industry 5.0 have paved the way for the implementation of new methodologies and technologies, including digital twins (DT) and extended reality (XR) tools. However, the increasing complexity of installations, combined with the need for external expertise during maintenance operations, calls for a rethinking of remote assistance methods. To address these challenges, our work focuses on utilizing these technologies to improve...

Intégrer LINEACT au sein de CESI pour un stage de recherche serait une formidable opportunité de contribuer à des projets innovants, tout en approfondissant mes compétences dans un environnement à la pointe de la transformation numérique et de l'industrie 4.0. Abstract This internship focuses on advancing the integration of AI into production lines by leveraging profilometer data to optimize waste reduction and enhance precision. This M2 internship aims to develop the step 4 of the project, whose goal is to integrate Artificial Intelligence (AI) into the production line to reduce waste using the profilometers data. The tasks assigned to the intern are as follows: • Clean the point cloud to only extract the front part and determine if the point cloud is incomplete • Match the CAD of the front part with its cloud point acquired by the laser profilometer. • Determine the key area used to match the back and front part of the product. • Creation of CAD back cover with defaults...

Intégrer LINEACT au sein de CESI pour un stage de recherche serait une formidable opportunité de contribuer à des projets innovants, tout en approfondissant mes compétences dans un environnement à la pointe de la transformation numérique et de l'industrie 4.0 Travaux de recherche proposésContexte : L'explosion de la robotique et de ses usages a conduit les fabricants de robots à développer leur propre logiciel de programmation pour doter leurs machines de capacités d'intelligence. Néanmoins, ces environnements de programmation, souffrent de certaines limites : ils sont très souvent propriétaires et ne sont donc pas ouverts pour accéder aux couches basses de programmation. Pour remédier à ces contraintes, les middleware robotiques sont apparus dès le début des années 2000. Le concept est simple : le middleware robotique est une surcouche logicielle, installable sur un système d'exploitation existant (type Linux ou Windows), qui contient en natif des outils et librairies génériques...

Scientific fields: Artificial Intelligence, Machine Learning, Feature Selection, Digital Health. Keywords: Feature Selection, Multimodal Data, Real-Time, Monitoring, Fall-detection, Health. Internship Topic Stress and emotion monitoring systems play a crucial role in mental health management, especially given the global rise in psychological disorders. Wearable devices equipped with sensors such as ECG (electrocardiogram), PPG (photoplethysmogram), EDA (electrodermal activity), and motion sensors provide a rich source of data for stress and emotion analysis. However, the high dimensionality and noise present in these multimodal datasets pose challenges for efficient processing and interpretability. Feature selection is essential for building robust and interpretable models. Recent advancements in explainable AI (XAI) emphasize the need to ensure that selected features provide understandable information about emotional and stress states, which strengthens trust and adoption by...