Multimodal learning using convolution neural network and Sparse Autoencoder

In the last decade, pattern recognition methods using neuroimaging data for the diagnosis of Alzheimer's disease (AD) have been the subject of extensive research. Deep learning has recently been a great interest in AD classification. Previous works had done almost on single modality dataset, su...

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Vydané v:	International Conference on Big Data and Smart Computing s. 309 - 312
Hlavní autori:	Vu, Tien Duong, Yang, Hyung-Jeong, Nguyen, Van Quan, Oh, A-Ran, Kim, Mi-Sun
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.02.2017
Predmet:	Alzheimer's disease autoencoder Biological neural networks Convolution convolutional neural network deep learning Feature extraction Magnetic resonance imaging MRI PET Positron emission tomography Support vector machines Three-dimensional displays
ISSN:	2375-9356
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