Website
http://dataportal.arc.gov.au/NCGP/API/grants/LP160101885
Funding Status
Closed
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Funded Activity Summary
Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enable improved event detection and classification in noisy time series to the benefit of many critical application areas beyond national security.Funded Activity Details
Start Date: 09-2017
End Date: 09-2019
Funding Scheme: Linkage Projects
Funding Amount: $204,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Applied Statistics | Pattern Recognition and Data Mining | Statistics
