Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
|
 |
Application of the Neural Networks Based on Multi-valued Neurons to Classification of the Images of Gene Expression Patterns
| |
|
Application of the Neural Networks Based on Multi-valued Neurons to Classification of the Images of Gene Expression Patterns
Igor Aizenberg5  , Ekaterina Myasnikova6 , Maria Samsonova6 and John Reinitz7
| (5) |
Neural Networks Technologies (NNT) Ltd., 155 Bialik st., Ramat-Gan, 52523, Israel |
| (6) |
Institute of High Performance Computing and Data Bases, 118 Fontanka emb., St.Petersburg, 198005, Russia |
| (7) |
The Department of Applied Mathematics and Statistics, The University at Stony Brook, Stony Brook, NY 11794-3600, USA |
Abstract
Multi-valued neurons (MVN) are the neural processing elements with complex-valued weights and high functionality. It is possible
to implement an arbitrary mapping described by partial-defined multiple-valued function on the single MVN. The MVN-based neural
networks are applied to temporal classification of images of gene expression patterns, obtained by confocal scanning microscopy.
The classification results confirmed the efficiency of this method for image recognition. It was shown that frequency domain
of the representation of images is highly effective for their description.
Fulltext Preview (Small, Large)
 References secured to subscribers.
|
|
|
|
|
|