论文信息 - Classification of the images of gene expression patterns using neural networks based on multivalued neurons with the minimal number of inputs

Classification of the images of gene expression patterns using neural networks based on multivalued neurons with the minimal number of inputs

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 gene expression images is highly effective for their description.

Igor N. Aizenberg | Constantine Butakoff | John Reinitz | Ekaterina Myasnikova | Maria Samsonova

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