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and interoperability, and efficient processing and management of time-series datasets and metadata originating from IoT sources (such as environment sensors and meters) closer to the data provider
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collaboration between the OU and Teledyne e2v (T-e2v), a world-leading manufacturer of scientific and industrial image sensors. The CEI is dedicated to conducting research into advanced imaging technologies
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quality, and real-time AI performance. This research hub, tackles the intricate challenges of cyber-disturbances and data quality in Edge Computing (EC) environments supporting AI algorithms. The role
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-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble
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with UAVs for tackling wildfires, including modular, scalable methods with respect to the volume of collected data, to the number of UAVs, data sampling rates, number of sensors, centralised
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and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected from in-service
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novel contributions to the field of computer vision and deep learning in smart manufacturing. These novel algorithms will then be integrated on to a mobile robotic system that will inform the design and
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Job title: Assistant Professor in Signal and Image Processing or Robotics School: School of Engineering & Physical Sciences Institute: Institute of Sensors, Signal and Systems Grade and Salary
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, path finding and routing algorithms, sense of direction, human computer interaction, cognitive navigation, intelligent mobility, and artificial intelligence. Sensor fusion and Signals of Opportunity We
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directly and relate them to structural and functional outcomes. In parallel, you will develop new sensors for intracellular potassium concentration leveraging AI based protein design algorithms. Techniques