Fig. 3 Online data augmentation expansion dataset
⑵ Data augmentation
Large-scale datasets can enhance the generalization ability[17] and robustness of target detection models[18]. The effects of data enhancement are as
follows: ⑴ Increase the amount of data for training to improve the
generalization ability of the model. ⑵ Increase the noisy data to
improve the robustness of the model and avoid overfitting[19]. Data augmentation can be divided into two
categories: ⑴offline augmentation, ⑵online augmentation. Online
augmentation enhances the acquired batch data, such as rotation,
translation, folding, etc. And is used in the case of a larger dataset
size.
In this paper, online augmentation is used to expand the surface defect
dataset, and the online data enhanced image is shown in Figure 3. After
data augmentation, surface images are obtained and divided into training
data set, validation data set and test data set according to the ratio
of 7:2:1.
Tab 1 Table of data set size and number of defects