Results demonstrate that their CNN outperform traditional feature-based methods in detecting JPEG steganography provided that the number of training data is huge.
not surprisingly, adding more layers causing trouble in training; this can be observed in Fig.  4 showing abnormally higher training errors achieved by a more complex 20-layer CNN, and there is no question that the validation performance also suffer. 