Abstract
In this study, we introduce two hybrid artificial neural network models with particle swarm optimization algorithm to diagnose diabetic retinopathy based on the Video-Oculography signals. The hybrid models use Discrete Wavelet Transform and Hilbert-Huang Transform separately to extract features from the signals. The classification performance of both models is analyzed comparatively. We show that the model based on Hilbert-Huang Transform exhibits better classification performance than the model based on the Discrete Wavelet Transform. (C) 2018 Elsevier Ltd. All rights reserved.
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Kapsamı
Uluslararası
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Type
Hakemli
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Index info
WOS.SCI
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Language
English
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Article Type
None
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Keywords
Video-oculography Diabetic retinopathy Wavelet transform Hilbert-Huang transform Artificial neural network Particle swarm optimization