DocumentCode :
583723
Title :
Using Neural Networks for Extended Detection
Author :
Cano, Lester A.
Author_Institution :
Sandia Nat. Labs., Albuquerque, NM, USA
fYear :
2012
fDate :
15-18 Oct. 2012
Firstpage :
246
Lastpage :
250
Abstract :
Extended Detection (ED) has become required especially when protecting high valued assets. Physical Protection Systems (PPS) usually integrate Detection, Delay, and Response (DDR) elements in a manner to assess threats at well defined perimeters. Situational Awareness (SA) beyond PPS perimeters requires the use of longer range sensors systems such as Radars or Unattended Ground Sensors which cover relatively large areas. Gathering such sensor data, especially in high noise environments poses a serious challenge to building reliable ED systems. The use of Neural Networks to merge sensor data and identify potential threats can make SA systems available for broader use.
Keywords :
neural nets; object detection; protection; sensors; PPS perimeters; detection delay and response; extended detection; neural networks; physical protection systems; reliable ED systems; sensor data; situational awareness; unattended ground sensors; Artificial neural networks; Magnetic sensors; Marine vehicles; Reliability; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Security Technology (ICCST), 2012 IEEE International Carnahan Conference on
Conference_Location :
Boston, MA
ISSN :
1071-6572
Print_ISBN :
978-1-4673-2450-2
Electronic_ISBN :
1071-6572
Type :
conf
DOI :
10.1109/CCST.2012.6393566
Filename :
6393566
Link To Document :
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