A convolutional neural network face recognition algorithm based on bootstrapping

Convolutional Neural Network models can be used to train a large amount of data for subsequent data analysis. This paper proposes a Convolutional Neural Network framework model based on Bootstrapping for Deep Learning and analysis of massive face data containing noise. According to the analysis of experimental results, it is concluded that the proposed Bootstrapping based Convolutional Neural Network framework model can achieve Deep Learning and subsequent prediction of large-scale noisy labeled facial data. It has the advantage of low computational cost and has achieved stateof- the-art results in various facial benchmark tests.