ODD : Online Deep anomaly Detection (ANR, 2023-…)
Chaire IA RAIMO : A Road toward safe Artificial Intelligence in MObility (ANR, 2020-2024)
DynaTeam : Dynamique de coordination d'équipe (ANR, 2023-…)
Partners : CETAPS, Équipe RI2C du LITIS
FAMOUS : Fair Multimodal Learning (ANR, 2023-…)
Partners : LIS, LHC, INT, Euranova
FINLAM : Foundation INtegrated models for Libraries Archives and Museum (ANR, 2023-…)
Partners : TEKLIA, BnF
SHARP : Machine Learning for Safe Vehicle Charging Points (ANR, 2023-…)
Partners : Citeos Solutions Digitales (VINCI Energies), GREYC
CoDeGNN : Convolution and Decimation for Graph Neural Networks (ANR, 2021-2025)
Partners : GREYC, LIFAT
MediSeg : Deep medical image segmentation: what’s next? (ANR, 2021-2025)
Partners : LMI, ImVIA, Équipe QuantIF du LITIS
MultiTrans : Gradual Multi Transfer Learning for Safe Autonomous Driving (ANR, 2021-2025) Partners : Équipe STI du LITIS, I3S, Valeo.ai
EXO-POPP : Optical Extraction of Handwritten Named Entities for the Marriage Certificates of the Population of Paris (1921-1946) (ANR, 2021-2024)
Main partner : LARHRA
CATCH : Automatic Understanding of Human Sensors Testimonials (ANR, 2021-2023)
Partners : Saagie, Atmo Normandie
LabCom L-Lisa : Common Lab LITIS-Saagie (ANR, 2021-2025)
Partner : Saagie
DeepART : Medical Image collection, segmentation and anonymization for DEEP learning in Adaptive Radiation Therapy (2020-2022)
Partners : Centre François Baclesse, Centre Henri Becquerel, GREYC
Partner : Eindhoven TU
AMCAS : Machine Learning for Understanding Secondary Atomization (2020-2022)
Partner : CORIA
THESIS : THermoplastic Erosion Shield for new generation Ice protection System (2019-2022)
Partners : Zodiac Aerosafety Systems (nowadays SAFRAN), Analyse and Surface, Dedienne Multi-plasturgy Group, IRSEEM, GPM, CORIA
Partners : UMR IDEES, UMI UMMISCO
APi : Taming the Beast of the Preimage in Machine Learning for Structured Data : Signal, Image and Graph (ANR, 2018-2023)PAUSE APi : in complement to ANR APi, this funding is from the national program for the urgent aid and reception of scientists in exile (PAUSE, from the Collège de France)
NormanD'eep : Deep learning and application (2018-2022)
Partner : GREYC
ASTURIAS : Newspaper image analysis (2018-2022)
Partners : GREYC, MIND group of LITIS
DeepInFrance : Machine learning with deep neural networks (ANR, 2018-2022)
Partners : INRIA Grenoble, I3S, GREYC, LIF-AMU, LIP6
LEAUDS : Learning to understand audio scenes (ANR, 2018-2022)
Partners : Netatmo, INRIA Nancy - Grand Est
ESCAPE : Exploring by Simulation Cities Awareness on Population Evacuation (ANR, 2017-2022)
Partners : UMR IDEES, UMI UMMISCO
DynACEV : Dynamics of Learning: Behaviour and Lived Experiences. The role of exploratory strategies (ANR, 2017-2022)
Partners : CETAPS, ISSUL (Lausanne), MIP, SOPESES (Nouvelle-Zélande), SPARC (UK)
OATMIL : Optimal Transport and Machine Learning (ANR, 2017-2022)
Partners : IRISA, Lagrange, Technicolor
HBDEX : Analysis of historical financial data (ANR, 2017-2022)
Partners : PSE, CAMS, IRISA
POPP : Project for the oceration of the Paris population census (1921-1946) (2020-2021) - voir démonstrateur ici
Partner : LARHRA
EurHisFirm : The European project aims at designing a world-class research infrastructure to collect, merge, extract, collate, align and share detailed historical high-quality firm level data for Europe (H2020 EU, 2018-2021)
Partners : Consortium of 16 European partners
Read E-Doc : Development of a system for extracting specific alphanumeric information from dematerialized container shipment slips (2019-2021)
Partner : Toshiba
Our PhD students in industry (CIFRE programs) with companies DataHertz, Lokad, TEKLIA, Weinig Luxscan, Actemium, SOLYSTIC, Itekube
PIVAJ (Plateforme d'Indexation et de Visualisation d'Archives de Journaux) is a software suite for automatic analysis and display of digitized historical newspapers.The offline part extracts sections, articles and text from the digitized images, to build structured METS/ALTO files.
DocExplore is a free software suite to build and display augmented books from digitization. DocExplore is WySiWyG, no XML knowledge required, and works on Windows, MacOs and Linux.