Publikationsansicht

SONAR DISCRIMINATION OF CYLINDERS FROM DIFFERENT ANGLES USING NEURAL NETWORKS (2007)

Abstract
This paper describes an underwater object discrimination system applied to recognize cylinders of various compositions from different angles. The system is based on a new combination of simulated dolphin clicks, simulated auditory filters and artificial neural networks. The model demonstrates its potential on real data collected from four different cylinders in an environment where the angles were controlled in order to evaluate the models capabilities to recognize cylinders independent of angles. 1.

Details der Publikation
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.29.1886
Quelle http://eivind.imm.dtu.dk/publications/1999/nonboe.icassp99.ps.gz
Mitarbeiter CiteSeerX
Archiv CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Typ text
Sprache Englisch