Abstract:
The model of a neural network based on metric methods of recognition represents the architecture of a neural network implementing metric methods of recognition. In such networks, the number of neurons, layers and connections, as well as the values of weights can be defined analytically using the initial conditions of a problem (the number of images, templates and attributes). The feasibility of defining network parameters and architecture allows rapid implementation of a network in the case of multitasking application. Finally, we consider multitasking application of neural networks based on metric methods of recognition under different conditions with separately computed classifiers.
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