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Low-Energy On-chip Pre-processing for Activity Recognition – LEOPAR
The emerging “Internet of Things” growth is faced with massive amounts of data to be transferred from connected portable devices to central computation units processing data from multiple sensors. Decreasing the energy consumption of the devices must be a priority to increase the battery lifetime. Since the wireless communication interface is the most energy-hungry parts of the sensor nodes, the LEOPAR project aims at determining the input data relevance to limit the amount of data to transmit.
Low energy neuromorphic devices based on spin wave scattering by topological spin texture – Neurowave
underpin the current revolution in artificial intelligence (AI), reshaping how society views, processes
Low Rank Approximations for Artificial Intelligence – LoRAiA
In a context of data being collected and exploited at huge scales, designing efficient machine learning tools that capture the complexity of data is one of the most important challenges of the decade.
Lorraine Artificicial Intelligence – LOR-AI
competitiveness. This project about Artificial Intelligence, led by the Université de Lorraine (UL), involves
Looking for relevant linguistic units to improve the intelligibility measurement of speech production disorders – RUGBI
In the context of the speech production disorders observed in ENT cancers, neurological, sensory or structural pathologies, the objective of the RUGBI project is to make improvements to the measurement of the intelligibility deficit.
Long Term MappINg for Urban Mobility – pLaTINUM
development of mobility applications for people or intelligent vehicles. These tasks that have been intensively [...] multi-sensors, of the world by a network of intelligent and communicating agents in order to develop [...] services dedicated to the mobility for people and intelligent vehicles.
Logic Elementary Gate Overstacked – LEGO
Logic Elements using Gate Overstacking
Light-transport Simulation and Machine Learning – LUCE
and based on learning methods and artificial intelligence, we propose to implement a new sampling and
