We consider the problem of information fusion frommultiple sensors of different types with the objective of improving the confidence of inference tasks, such as object classification, performed from the data collected by the sensors. We propose a novel technique based on distributed belief aggregation using a multiagent prediction market to solve this information fusion problem. To monitor the ...

PURPOSE We sought to analyze the results of arterial injury management in a busy metropolitan vascular unit and risk factors associated with mortality and morbidity. PATIENTS AND METHODS We analyzed 120 patient with arterial injury treated between year 2000 and 2010 at the University Clinical Center of Kosovo. Seven of these years were prospective and three retrospective study. RESULTS The ...

Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the event’s outcome. We consider an analogous problem of information fusion from multiple sensors of different types with the objective of improving the confidence of inference tasks, such as object classification. We develop a multi-agent prediction market-base...

Mechanical systems or robots to assist landmine detection are expected to greatly improve quality of humanitarian demining tasks. These new systems could provide: i) safer operation; ii) advanced methods for automatic target recognition and discrimination; iii) consistent performance with less influence of “human-factors”; iv) better detection performance, i.e., higher probability of detection ...

We present the sensor-fusion results obtained from measurements within the European research project ground explosive ordinance detection (GEODE) system that strives for the realisation of a vehicle-mounted, multi-sensor, anti-personnel landmine-detection system for humanitarian de-mining. The system has three sensor types: a metal detector (MD), an infrared camera (IR), and a ground penetratin...