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...

Full description

Bibliographic Details

Published in:	International Conference on Big Data and Smart Computing pp. 309 - 312
Main Authors:	Vu, Tien Duong, Yang, Hyung-Jeong, Nguyen, Van Quan, Oh, A-Ran, Kim, Mi-Sun
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.02.2017
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!