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National Projects

ANR PerfAnalytics (2021-2024)

PPR Antibiorésistance: structuring tool “PROMISE” (2021-2024)

CASDAR CARPESO (2020-2022)

Inria Exploratory Action CAcTUS (2020-2023)

Institut de Convergences #DigitAg (2017-2023)

Inria Project Lab  HPC-BigData (2018-2022)

PIA Floris’tic (2015-2018)

CIFRE INA/Inria (2013-2016) on large-scale supervised content-based retrieval

PIA Datascale (2013-2015)

PIA X-Data (2013-2015)

EDF: Privacy Preserving Data Mining in P2P Networks (2013-2015)

Mastodons (CNRS INS2I) on data management for plant phenotyping (2012-2015)

RTRA Pl@ntNet (2009-2013)

CIFRE INA/Inria (2011-2013) on content-based mining of visual objects in large collections

ANR OTMedia (2010-2013)

Data Publica (2010-2013)

ANR VERSO DataRing (2008-2012)

Permanent link to this article: https://team.inria.fr/zenith/projects/national-projects/

Inria Exploratory Action CAcTUS (2020-2023)

CAcTUS is an Inria exploratory action led by Alexis Joly (Inria research director) with the participation of Joaquim Estopinan (Inria doctoral student), Pierre Bonnet (botanist at CIRAD), François Munoz (ecologist / modeler at LECA), Maximilien Servajean (researcher in machine learning at LIRMM) and Joseph Salmon (professor of statistical learning at the University of Montpellier). The …

Institut de Convergences #DigitAg (2017-2023)

#DigitAg brings together in a partnership of seventeen actors (public research and teaching organizations, transfer actors and companies) with the objective of accelerating and supporting the development of agriculture companies in France and in southern countries based on new tools, services and uses. Based in Montpellier with an office in Toulouse and Rennes and led …

IPL HPC-BigData

The IPL HPC-BigData is a four year project (2018-2022) funded by Inria. The goal of this HPC-BigData IPL is to gather teams from the HPC, Big Data and Machine Learning (ML) areas to work at the intersection between these domains. Research is organized along three main axes: high performance analytics for scientific computing applications, high …