Dafni Stampouli

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Given the unbounded analysis of situations, events, users, resources, and missions; it is obvious that uncertainty is manifested by the nature of application requirements. In this panel, we seek discussions on methods and techniques to intelligently assess the problem of HLIF uncertainty analysis to alleviate high-performance statistical computational(More)
– There is an identified need for systems to combine information from hard (electronic) and soft (human) sensors. In this paper we report an ongoing development of a centralised framework to provide data and information fusion for interoperability of emergency services. Issues relating to situation and threat assessment are discussed and fusion processes(More)
High-Level Information Fusion (HLIF) utilizes techniques from Low-Level Information Fusion (LLIF) to support situation/impact assessment, user involvement, and mission and resource management (SUM). Given the unbounded analysis of situations, events, users, resources, and missions; it is obvious that uncertainty is manifested by the nature of application(More)
In a crisis management context, situation awareness is challenging due to the complexity of the environment and the limited resources available to the security forces. The different emerging threats are difficult to identify and the behavior of the crowd (separated in groups) is difficult to interpret and manage. In order to solve this problem, the authors(More)
The ability to compare a vague description of a person with a known dataset of people is an invaluable tool for various security related applications. This notion is built upon to allow the fusion of various descriptions of the same person to create a suspect description, which is then compared against the dataset of known people. Two different methods have(More)
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