Abstract
In this paper, we use the image data in the dataset-FER2013 as a sample. First, we format the CSV file in the dataset. After finding that there is a large difference in the number of different types of pictures, in order to compare and verify the impact of the number difference on the results, we enhanced the data set through the proposed data augmentation method, so that the data set can meet the experimental needs. After that, by understanding the artificial intelligence learning algorithms at home and abroad, we decided to establish a training model using AlexNet network, and divided the pictures to be identified into three groups with different numbers: original data set, down sampling data set and dataset with data augmentation. In the experiment, we achieves 52.3% accuracy after data enhancement, and 66.9% accuracy using the down sampling dataset.
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