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Deep Learning for Prediction of Judicial Outcome – LAWBOT
LAWBOT is first, an applied research project in law, on the use of automated natural language processing techniques. The LAWBOT project aims to create an artificial case-law intelligence capable of predicting the judicial outcome for a given case, by imitating the decisions previously rendered by th
Deep learning for automatic image-based biomonitoring of aquatic ecosystems – BIOINDIC-IA
Aquatic ecosystems are facing many anthropogenic pressures, highlighting the urgent need for developing innovative ecological diagnostic tools supporting the selection of robust management responses. Current diagnostic tools are able to estimate the ecological status from taxonomy-based (i.e. list o
Design of a versatile in silico fragment-based drug design tool – UniversalF2D
Fragment-Based Drug Design (FBDD) is an approach widely developed and used in academic laboratories and pharmaceutical companies for the past twenty years. Nowadays, several drugs approved by the FDA or advanced in clinical trials were discovered from FBDD. To go further and gain in time and efficie
Detection of False Data Injection Attacks on the ADS-B protocol in the civil and military air traffic control – DApIA
The DApIA project aims at developing capabilities to detect False Data Injection Attacks (FDIA) using Machine Learning components on air surveillance data from the ADS-B protocol. The objective of FDIA attacks is to corrupt the semantics of the surveillance data while preserving the correct syntax
Digital Materials - An industrial Reality In Motion – RealIMotion
One of the European Union's climate change objectives is to achieve net-zero greenhouse gas emissions by 2050. This goal puts significant pressure on the metallic materials industry, a major contributor to fossil CO2 emissions, necessitating powerful digital strategies to design, improve, and calibr
ECOlogical and ECONomic trade-offs of VAluable invaSions: Insights, Opportunities and Novel Solutions – EconVasions
Invasive alien species (IAS) pose serious threats to biodiversity and ecosystem health, affecting human well-being. Many of those species have multiple roles, providing both benefits and burdens to ecosystems and stakeholders. Managing these Multiple-Role invasive species (MR-IAS) involves complex t
EUROCC - National Competence Centres in the framework of EuroHPC – EUROCC
The Competence Centre provide skills mapping, training and service offerings for HPC, HPDA (High Performance) Data Analytics) and AI (Artificial Intelligence). The Centre offers access to its offers and services: Awareness, Training, user support, marketplace... CC-FR, the NCC France has been estab
EXploitation of planT wastes as a sustainable souRce of Anti-inflammatory Compounds for Therapeutics – EXTRACT
Chronic inflammation is associated with a broad spectrum of diseases. To combat this complex process, there is today a renewed interest in medicinal plants. It is however important to diversify biological resources in order to avoid any risk of depleting the widely used native European plants, like
Ecole Française de l'Intelligence Artificielle - MIAI Institute
L'objectif d'EFELIA-MIAI (ANR-22-CMAS-0005) est d'élargir à tous niveaux et disciplines la formation à l'IA en promouvant son usage de manière responsable en cohérence avec les enjeux sociétaux et environnementaux. Le projet vise aussi le développement de l'acculturation à l'IA dans les lycées, L
Ecole Française de l'Intelligence Artificielle - Site Côte d'Azur
Coordonné par l'Université Côte d’Azur, EFELIA Côte d’Azur s'appuie sur un consortium composé d'Inria, du CNRS, de l'Inserm, d'EURECOM et de SKEMA Business School. La direction scientifique du projet est assurée par Lucile Sassatelli, Professeure des universités en informati
