CE23 - Intelligence Artificielle

Heterogeneity of data and methods: A unified collaborative framework for interactive temporal data analysis – HERELLES

Submission summary

In a break with current approaches, each based on an analysis paradigm, the HERELLES scientific program aims to define an operational theoretical framework that allows the combination and collaboration of different analysis paradigms and allows strong interaction with the expert for the extraction of knowledge from heterogeneous multi-temporal data. We aim for an approach that will allow collaboration between supervised or unsupervised methods through information transfers (clusters will be used to create learning data or to increase their size, learning data will be used to help validate and thematize clusters...) extracted from different but complementary time data. This collaboration will be controlled by the expert, who will intervene to incrementally add new knowledge. Thematic validation in remote sensing.

Project coordinator

Monsieur Pierre Gancarski (Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357))

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

TETIS Territoires, Environnement, Télédétection et Information Spatiale
ICUBE Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357)
LIFO EA 4022 LABORATOIRE D'INFORMATIQUE FONDAMENTALE D'ORLÉANS
GREYC Groupe de recherche en Informatique, Image, Automatique et Instrumentation de Caen
MIA Mathématique et Informatique Appliquées

Help of the ANR 739,546 euros
Beginning and duration of the scientific project: November 2020 - 48 Months

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