Enhanced models in deep image steganography
Ruxandra Fratila, Luciana Morogan · 2021
Seeking to take advantage of the innovations brought by machine learning, a field in a continuous movement and development, the present paper aims to enhance a practice that has been used since ancient times: steganography. Thereby, we targeted the implementation of a system aimed to hide image-type messages with the aid of deep neural networks. We followed a baseline model designed according to the recommendations stated into the state-of-the-art section. Then, we progressively developed three new models, each adding a new improvement on top of the previous one.