NDLI: Hostile intent identification by movement pattern analysis: Using artificial neural networks

Content Provider	IEEE Xplore Digital Library
Author	Biswas, Souham Nene, Manisha J.
Copyright Year	2014
Description	Author affiliation: J. K. Institute of Applied Physics & Technology, University of Allahabad, Allahabad, India (Biswas, Souham) \|\| Dept. of Applied Mathematics and Computer Engineering, Defence Institute of Advanced Technology, Defence R&D Organization, Ministry of Defence, Pune, India (Nene, Manisha J.)
Abstract	In the recent years, the problem of identifying suspicious behavior has gained importance and identifying this behavior using computational systems and autonomous algorithms is highly desirable in a tactical scenario. So far, the solutions have been primarily manual which elicit human observation of entities to discern the hostility of the situation. To cater to this problem statement, a number of fully automated and partially automated solutions exist. But, these solutions lack the capability of learning from experiences and work in conjunction with human supervision which is extremely prone to error. In this paper, a generalized methodology to predict the hostility of a given object based on its movement patterns is proposed which has the ability to learn and is based upon the mechanism of humans of “learning from experiences”. The methodology so proposed has been implemented in a computer simulation. The results show that the posited methodology has the potential to be applied in real world tactical scenarios.
Starting Page	439
Ending Page	444
File Size	297756
Page Count	6
File Format	PDF
ISBN	9781479976829
e-ISBN	9781479976836
DOI	10.1109/PDGC.2014.7030786
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-11
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Neurons Maritime Training data Artificial Intelligence Neural Networks Hostility Indexes Object recognition Biological neural networks Defence
Content Type	Text
Resource Type	Article

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