Special Issue on Machine Learning and Sensor Fusion Techniques for Surveillance and Monitoring Applications
نویسنده
چکیده
The recent advances in the smart sensor technology and proliferation of their availability in conjunction with ubiquitous communication platforms have tremendously enabled researchers in surveillance and situational understanding area to propose and build cutting edge Monitoring and Surveillance applications with high quality and fidelity. The purpose of this special issue is to provide details on some of these developments of advanced techniques and tools, which would cover areas concerned with monitoring, modeling, control, and the management of surveillance data. Further, although the primary target audiences for this issue are the researchers in surveillance and monitoring techniques, the researchers in areas of machine learning, cognitive intelligence, and image processing would also find the papers covered in the issue equally beneficial. The issues contains four papers selected after a very strict review process towards providing the readers with novel, well presented, and high quality research contributions. The issue contains a paper from Dr. Erik Blasch and his colleagues that describes their lat-est work, Qualia-based Exploitation of Sensing Technology (QuEST). QuEST, is an approach to create a cognitive exoskeleton to improve human-machine decision quality. In this paper, authors presented QuEST-motivated man-machine information fusion with an example for multimedia narratives. In QuEST, the user-based situation awareness includes both elements of external sensory perception and internal cog-nitive explanation. Further, the paper outlines QuEST elements and tenets towards a reason
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