2. Data Padding

Data padding is one of the ways to resize learning images by adding spaces and meaningless symbols to the end of existing data. As a result of learning without data padding in the augmentation conducted during the 2nd preprocess of this study, very low accuracy (25%) and high loss values were identified (Table 4). This is because the edges of the image data are distorted by the data enhancement. Accordingly, in this study, the image data were padded to prevent distortion of the edges of the data.

**Table 4.** Data Augmentation and Learning Results.


During the 1st preprocessing, during which channel setup and data padding were performed, image data of 150 × 150 px in GRAYSCALE format were obtained as follows: There are 4900 road and wet road image data and 4900 snow road and black ice image data (Table 5).


**Table 5.** Number of data through 1st preprocessing.
