Prediction of Number of Accesses by Thumbnail Image Classification on Video Sites

What is it about?

In In recent years, video sites such as YouTube have become popular on the Internet, and it is a fact that Internet users spend a lot of time watching videos on these video sites every day. It is thought that users select the sites and channels they want to view based on some criteria such as need or interest, but the selection criteria are not clear, and it is necessary to provide some kind of indicator. In this paper, we propose that thumbnail images may be one of the factors when viewers select a video from among a large number of video sites and channels. Thumbnail images are a standard that channel operators can actively participate in creating, and we hypothesize that the quality of thumbnail images can increase the number of accesses. As a result of testing, we found that it was possible to predict the number of accesses from thumbnail images.

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