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Fusion of Heterogeneous Components by Articial Intelligence – FUSCHIA
INPIXAL specializes in collecting and processing images from drones for ISR (Intelligence, Surveillance, Reconnaissance) missions for military and civil purposes. The experience accumulated during experiments or operational missions for the DGA or institutional clients shows that, while the performa
Structured, Consolidated and Unified Interactive Dialogue for Robot Task Performance – DISCUTER
Robots that can learn new concepts and be instructed to carry out novel tasks simply via conversation---as opposed to full demonstration or hard-coding by experts---will be valuable in a wide array of contexts in the future, from performing construction tasks on factory floors to engaging in physica
Treatment of fake news and informational vagueness: a hybrid approach between deep learning and symbolic AI – HYBRINFOX
The HYBRINFOX project aims to contribute to the fight against online misinformation by studying and developing possible synergies between symbolic AI and deep learning approaches for the detection of fake news (aka. infox). The main lever is the identification of vague information, likely to introdu
Artificial Intelligence for the detection and geolocation of an illegitimate electromagnetic source – DEPOSIA
DEPOSIA focuses on the detection and geolocation of various radio frequency signal sources in order to thwart attacks on connected systems and infrastructures. The sources considered are elements which by their characteristics or their position, present an illicit character and which threaten the pe
Robust Machine Learning for Unmanned Traffic Management Systems – ROMEO
ROMEO is a project which aims to develop a robust system for anomaly detection in drone trajectories based on the use of physics informed neural networks, statistical methods for anomaly detection and quantification of uncertainty through conformal inference methods. In this consortium Thales will b
