[tmabraham]

Because you can take advantage of pretrained CNNs and perform transfer learning, which is significantly more data-efficient than training from scratch, which is what you'd likely have to do with raw digital signals. This paper is not unique in this approach and many papers have obtained SOTA results by processing digital signals as images.

[jononor]

The complexity/dimensionality of the data representation is increased considerably when going from time series to images of said time series. Sure one can then use transfer learning to manage this complexity. But do you have any references for this approach being more data effective overall?