Random neural network recognition of shaped objects in strong clutter

Hakan Bakircioğlu; Eroł Gelenbe; Larry Carin

doi:10.1007/bfb0020277

Random neural network recognition of shaped objects in strong clutter

Hakan Bakircioğlu, Eroł Gelenbe, Larry Carin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

In this paper we propose a neural approach based on the Random Neural Network (RNN) model (Gelenbe 1989, 1990, 1991, 1993 [3, 4, 6, 5]), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	961-966
Number of pages	6
ISBN (Print)	3540636315
DOIs	https://doi.org/10.1007/bfb0020277
State	Published - Jan 1 1997
Externally published	Yes

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10.1007/bfb0020277

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title = "Random neural network recognition of shaped objects in strong clutter",

abstract = "In this paper we propose a neural approach based on the Random Neural Network (RNN) model (Gelenbe 1989, 1990, 1991, 1993 [3, 4, 6, 5]), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.",

author = "Hakan Bakircioğlu and Ero{\l} Gelenbe and Larry Carin",

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Random neural network recognition of shaped objects in strong clutter. / Bakircioğlu, Hakan; Gelenbe, Eroł; Carin, Larry.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 1997. p. 961-966.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Random neural network recognition of shaped objects in strong clutter

AU - Bakircioğlu, Hakan

AU - Gelenbe, Eroł

AU - Carin, Larry

N1 - Generated from Scopus record by KAUST IRTS on 2021-02-09

PY - 1997/1/1

Y1 - 1997/1/1

N2 - In this paper we propose a neural approach based on the Random Neural Network (RNN) model (Gelenbe 1989, 1990, 1991, 1993 [3, 4, 6, 5]), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.

AB - In this paper we propose a neural approach based on the Random Neural Network (RNN) model (Gelenbe 1989, 1990, 1991, 1993 [3, 4, 6, 5]), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.

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BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag

ER -

Random neural network recognition of shaped objects in strong clutter

Abstract

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