Applying data mining to false alarm reduction in an aviation explosives detection system
Security Technology（2010）
摘要
Data mining techniques were applied for the reduction of false positives in aviation explosives detection CT (computed tomography) imaging systems. An inductive post-detection classifier (PDC) was trained, implemented, and fielded. The PDC can only eliminate alarms generated from the existing detection system - it does not detect new alarms.
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关键词
aerospace industry,computerised tomography,data mining,explosives,learning (artificial intelligence),object detection,pattern classification,aviation explosives detection,classifier voting,computed tomography,data set training,false alarm reduction,false positive,post detection classifier,aviation security,classification,image processing,robustness,voting,classification algorithms,learning artificial intelligence,correlation
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