Computational intelligence in explosive hazard detection

Computational intelligence in explosive hazard detection

24 December 2015, SPIE Newsroom. DOI: 10.1117/2.1201512.006239 Uncountable deaths and injuries to civilians and soldiers are inflicted worldwide by explosive hazards (EHs). Since 2008, EH attacks in Afghanistan have wounded or killed approximately 10,000 US soldiers, and globally these devices cause on average 310 deaths and 833 wounded per month.1 Therefore, new sensors, mathematics, algorithms for signal processing, and techniques to intelligently combine (fuse) all of this information are needed to address the problem. No single sensor is currently able to accurately detect all explosive hazards in different contexts and environments. It is critical that we research and identify sensors that either directly detect hazards and/or help us identify context. We also require advanced features and classifiers to represent and detect explosive hazards within these individual sensors. Ultimately, we need data fusion…


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