Influence of dropout and dynamic receptive field operations on convolutional networks

Abstract

The method and the experiments which have been performed in order to struggle with coadaptation and to improve generalization abilities of networks with the help of two techniques: dynamic receptive fields and dropout have been presented of the article. It is an effective approach for networks training. The use of the method, combining the dropout technique and dynamic receptive fields, allows to reduce the generalization error and prevents the co-adaptation of neurons