The University of Southampton
University of Southampton Institutional Repository

Using artificial bat sonar neural networks for complex pattern recognition: recognizing faces and the speed of a moving target

Dror, I.E., Florer, F.L., Rios, D. and Zagaeski, M. (1996) Using artificial bat sonar neural networks for complex pattern recognition: recognizing faces and the speed of a moving target Biological Cybernetics, 74, (4), pp. 331-338.

Record type: Article

Abstract

Two sets of studies examined the viability of using bat-like sonar input for artificial neural networks in complex pattern recognition tasks. In the first set of studies, a sonar neural network was required to perform two face recognition tasks. In the first task, the network was trained to recognize different faces regardless of facial expressions. Following training, the network was tested on its ability to generalize and correctly recognize faces using echoes of novel facial expressions that were not included in the training set. The neural network was able to recognize novel echoes of faces almost perfectly (above 96% accuracy) when it was required to recognize up to five faces. In the second face recognition task, a sonar neural network was trained to recognize the sex of 16 faces (eight males and eight females). After training, the network was able to correctly recognize novel echoes of those faces as 'male' or as 'female' faces with accuracy levels of 88%. However, the network was not able to recognize novel faces as 'male' or 'female' faces. In the second set of studies, a sonar neural network was required to learn to recognize the speed of a target that was moving towards the viewer. During training, the target was presented in a variety of orientations, and the network's performance was evaluated when the target was presented in novel orientations that were not included in the training set. The different orientations dramatically affected the amplitude and the frequency composition of the echoes. The neural network was able to learn and recognize the speed of a moving target, and to generalize to new orientations of the target. However, the network was not able to generalize to new speeds that were not included in the training set. The potential and limitations of using bat-like sonar as input for artifical neural networks are discussed.

Full text not available from this repository.

More information

Published date: 1996

Identifiers

Local EPrints ID: 18335
URI: http://eprints.soton.ac.uk/id/eprint/18335
ISSN: 0340-1200
PURE UUID: d75908cf-8494-4b27-ac7d-da6275e6a5af

Catalogue record

Date deposited: 11 Jan 2006
Last modified: 17 Jul 2017 16:36

Export record

Contributors

Author: I.E. Dror
Author: F.L. Florer
Author: D. Rios
Author: M. Zagaeski

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×