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There is growing UK and international interest in networked sensing and autonomous collaborative platforms, where multiple airborne sensors co-operate to collect and exploit data. In contrast
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resilient infrastructure? Would you like to integrate advanced AI techniques with heterogeneous UAV-based sensor data for the inspection and maintenance of critical transportation infrastructure, addressing
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algorithms that can tightly integrate physical hardware, sensors, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining
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role involves designing and integrating real-time software algorithms with robotic hardware, including perception, control, communication, and safety modules to enable safe, precise, and reliable remote
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department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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on the development of new sensor concepts, their experimental characterisation, the development of suitable methodologies and systematic validation under realistic operating conditions. This includes the setup
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 14 days ago
: Large-Space Gaze Analysis via Multi-camera System for Social Interactions” to develop datasets and algorithms to capture and analyze eye gaze. About the project We are supporting the development of highly
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 6 days ago
to advancing algorithms for human-centered robots: robots that are not working autonomously in isolation, but that instead react, interact, collaborate, and assist humans. To do so, these robots need
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and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities