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Proceedings Paper

A novel approach to prevent 9/11/2001 events using artificial neural networks and decision support systems
Author(s): Arunkumar Srinivasan; Murugesan K Subramani; Abhijit S. Pandya
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Paper Abstract

The ability to detect objects from image sequences and estimate their trajectory is useful in many applications like satellite tracking, missile guidance and interception. This paper proposes a reliable and an effective application for preventing loss of lives on event of airline crashes similar to the one on 9/11/2001. This contribution uses the MixeD algorithm for object detection, velocity estimation and the trajectory of the moving object in the spatiotemporal domain. The case study of the 9/11 event shows that the proposed method could have helped the authorities alert the people inside the towers far in advance about the hostile situation and could have saved a few more lives.

Paper Details

Date Published: 8 August 2003
PDF: 7 pages
Proc. SPIE 5072, Technologies, Systems, and Architectures for Transnational Defense II, (8 August 2003); doi: 10.1117/12.502310
Show Author Affiliations
Arunkumar Srinivasan, Florida Atlantic Univ. (United States)
Murugesan K Subramani, Florida Atlantic Univ. (United States)
Abhijit S. Pandya, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 5072:
Technologies, Systems, and Architectures for Transnational Defense II
Mark K. Hamilton; Vince C. Boles, Editor(s)

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