Type annonces : Proposition de poste

Generative Few-Shot Learning using Mixture-of-Experts Transformers for 3D Skeleton-based Human Action Recognition

test

STAGE MASTER Scientific fields: Computer science, Artificial Intelligence, Computer Vision Keywords: Generative Few-Shot Learning; Transformers; Mixture-of-Experts; RGB+D Datasets; Human-System Interaction (HSI) Research interest: Computer Vision; Machine Learning; Deep Learning Research work: Deep Learning Models for 3D Skeleton-based Human Action Recognition 3D Skeleton-based Human Action Recognition (HAR) [1], [2] is fundamental…

Lire la suite

Geometric Deep Learning

test

A postdoc position in geometric deep learning at ICube laboratoire, University of Strasbourg. * Work description In the framework of a binational, tri-institutional project titled HuMoCar: Realistic Human Models for Care Robots for Aged People (October 2021 – October 2025), our objective is to improve the robustness of vision and…

Lire la suite

Estimation des fluctuations du spectre cosmologique de puissance de la raie de l’hydrogène neutre (21cm) durant l’époque de réionisation.

test

Stage M2 Contexte, candidature et profile recherché : Ce stage aura lieu entre le laboratoire SATIE (Systèmes et application des technologies de l’information et de l’énergie), l’IAS (Institut d’astrophysique spatiale) et le L2S (Laboratoire des signaux et systèmes) de l’université Paris Saclay. Il entre dans le cadre du GT ICR…

Lire la suite

AI for Galaxies and Planetary Nebulae Detection and Classification from Astronomical Images

test

Project description: Artificial intelligence has significantly advanced various aspects of astronomy. These advancements include adaptive optics for telescopes, fast universe simulations, space mission planning, warning systems, and real-time analysis of phenomena such as supernovae and asteroid appearances. The primary goal of this project is to develop machine learning techniques, such…

Lire la suite

Analyses statistiques de grands jeux de données spectrales de phénotypage : application à la discrimination entre stress hydrique et stress azoté

test

Lieu : INRAe / Université de Bourgogne, Dijon Encadrants : Walid Horrigue, Frédéric Cointault et Jean-Baptiste Thomas Durée du stage : 5 mois Dates : Mars à juillet 2025 Formation ciblée : Master en mathématiques et applications, master en statistiques et apprentissage, MAS … Candidature : Envoyer une lettre de…

Lire la suite

Image Super-Resolution using Diffusion Models from Synthetic Spectral Data

test

Application: Send motivation letter, CV, track record and recommendations by email at jean-baptiste.thomas@u-bourgogne.fr AND Abdelhamid-Nour-Eddine.Fsian@u-bourgogne.fr before the 15th of January 2025. Context: This project takes place at Lab IMVIA (https://imvia.u-bourgogne.fr/) at Université de Bourgogne. The Spectral Filter Arrays camera technology was developed over a decade at IMVIA, and recent research…

Lire la suite