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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	International Conference on Big Data and Smart Computing S. 309 - 312
Hauptverfasser:	Vu, Tien Duong, Yang, Hyung-Jeong, Nguyen, Van Quan, Oh, A-Ran, Kim, Mi-Sun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.02.2017
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!