Decision fusion in neural network ensembles

We present a comparison between different combining techniques in neural network ensembles. The main focus of this paper is on a new architecture that can be used in combining neural network ensembles. This architecture is based on training two neural networks to perform the aggregation. One network...

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Hauptverfasser: Wanas, N.M., Kamel, M.S.
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description We present a comparison between different combining techniques in neural network ensembles. The main focus of this paper is on a new architecture that can be used in combining neural network ensembles. This architecture is based on training two neural networks to perform the aggregation. One network is trained to establish a confidence factor for each member of the ensemble for every training entry. The other network performs the aggregation of the ensemble to present the final decision. Both these networks evolve together during training. This approach is compared with standard fixed and trained combining schemes.
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Clouds
Gaussian distribution
Glass
Image databases
Intelligent networks
Neural networks
Remote sensing
Satellites
Testing
Voting
title Decision fusion in neural network ensembles
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