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AI-Driven Work Transformations in Creative and Cultural Industries – AI-CCI
In the contemporary landscape, characterized by the emergence of cutting-edge generative artificial intelligence, there is a growing apprehension regarding the impact of these technologies on the quality of work. The International Labour Organization (Gmyrek et al., 2023) issues a cautionary note, h
AI-Enhanced eDNA Solutions for Comprehensive Marine Biodiversity Monitoring and Reporting – ADNeIA
Human-induced pressures and climate change are having profound and growing impacts on marine ecosystems, making the continuous monitoring of biodiversity and ecological status increasingly vital. Effective monitoring requires the development, modeling, interpretation, and mapping of ecological inven
AI-aided FEC code design and decoding – AI4CODE
The AI4CODE project brings together 6 research team with strong expertise in the design, decoding and standardization of forward-error-correction codes. The aim is to develop skills in artificial intelligence and machine learning, and to explore how learning techniques can contribute to the improvem
AI-enabled Digital Pathology for Spatially Resolved Molecular Profiling – DAFNI
Le cancer est la principale cause de décès dans le monde. Ces derniers temps, les avancées dans le domaine de la médecine de précision ont modifié les normes de traitement du cancer en proposant de nouveaux plans de traitement personnalisés aux résultats prometteurs. Cette spécification du traitemen
AI-enabled MUltimodal SEmantic COMmunications and COMputing – MUSE-COM^2
MUSE-COM^2 aims to develop and validate a novel system for AI-empowered multimodal communications considering semantics of individual modalities jointly optimized with the processing of the modalities in multi-access/mobile edge computing (MEC) servers. Unlike conventional semantic and goal-oriented
AI.iO Artificial Intelligence in Orléans: Learning from heterogeneous data and expert knowledge. Applications in geological and environmental sciences – AI.i0 PhD Fellowship
The University of Orléans benefits from an important research environment in Artificial Intelligence (AI) with both fundamental and applied research activities. It is supported by three laboratories: LIFO (Laboratoire d’Informatique Fondamentale de l’Université d’Orléans), IDP (Institut Denis Poisso
AI@IMT Responsible AI for Industry and Society – AI@IMT
This submission outlines the Institut Mines-Télécom (IMT) ambition to realise the strategic objective of enhancing its research agenda in the priority area of Artificial Intelligence and expanding its already substantial PhD program. In line with its 2018-2022 Strategic Plan, IMT aims to expand its
ARTIFICIAL INTELLIGENCE AND ALGORITHMIC COLLUSION (AIAC) – AIAC
The rise of AI and automated pricing algorithms prompts questions about their market impact. It's hypothesized that these algorithms could facilitate collusion by optimizing utility, much like rational economic agents. This potential has been explored in contexts such as the European Digital Markets
ARTIFICIAL INTELLIGENCE FOR INDENTIFICATION OF WOOD AND CHARCOAL IN ARCHAELOGICAL AND PALAEOLOGICAL PERSPECTIVE – AI-WOOD
Anthracology is a robust method of studying forest stands and their transformation as a result of climatic changes or human practices, but also the uses of wood as fuel and material. This method is based on the botanical identification of wood and charcoal preserved in archaeological sites. It is b
ARTificial Intelligence-based Cloud network control – ARTIC
Communication networks are being impacted by three major trends: (i) the cloudification, cloud IP traffic will become in the next years the most part of Internet traffic; (ii) the consolidation of IP video as dominant application, thanks to the growth of live streaming and virtual-augmented reality;
