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Image Recognition on the Neural Network Based on Multi-Valued Neurons

9 years 11 months ago
Image Recognition on the Neural Network Based on Multi-Valued Neurons
Multi-valued neurons are the neural processing elements with complex-valued weights, huge functionality (it is possible to implement on the single neuron arbitrary mapping described by partially defined multiple-valued function), quickly converged learning algorithms. Such features of the multi-valued neurons may be used for solution of the different kinds of problems. Neural network with multi-valued neurons for image recognition will be considered in the paper. Such a network with original architecture analyzes the phases of the Fourier spectral coefficients corresponding to the low frequencies. Quickly converged learning algorithm and huge functionality of multi-valued neurons allow to get 100% successful recognition of the different classes of images including the blurred and corrupted ones. Simulation results are presented on the example of face recognition.
Igor N. Aizenberg, Naum N. Aizenberg, Constantine
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Igor N. Aizenberg, Naum N. Aizenberg, Constantine Butakoff, Elya Farberov
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