Dynamical Change of the Perceiving Properties of Neural Networks as Training with Noise and Its Impact on Pattern Recognition.
Roman Nemkov · 2014
Abstract. General parameters of convolutional networks (kernels) are set in the learning process. Also in addition to the method of training the quantity of information that is passed through the kernel influences the quality of setting. This quantity of information depends on the size of training sample and the concentration of receptive fields. You can increase the concentration of the re-ceptive fields for a fixed training set size due to the multilayer coating of arbitrary maps with fields of different types, that will be equivalent to the use of noisy training sample. This can increase the networks performance in the test.