Abstract:In this paper, a semi-supervised classification algorithm that is based on weighted pseudo labeled data and mutual learning is proposed. The purpose of our method is to improve the classification performance of semi-supervised learning models and rectify the incorrect pseudo labels in the process of training. Specifically, the algorithm is built with a deep convolutional neural network and an ensemble learning model. First, output smearing is employed to construct different training sets and perform model init… Show more
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