Steganography is the art of concealing information in a cover media in such a way that the
presence of the information is unknown. Digital image steganography accomplishes the …

The rapid-developing Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …

Recently, extensive research has revealed the enormous potential of deep learning in the
application of image steganography. However, some defects still exist in previous studies on …

Image steganalysis is a technique for detecting data hidden in images. Recent research has
shown the powerful capabilities of using convolutional neural networks (CNN) for image …

Digital steganography has a long history, starting to be developed in the 90s until now. The
main aspects of early steganography are security, imperceptibility, and payload. Security is …

Multi-class pest detection is one of the crucial components in pest management involving
localization in addition to classification which is much more difficult than generic object …

Recently, generative steganography that transforms secret information to a generated image
has been a promising technique to resist steganalysis detection. However, due to the …

We present a system to hide a full color image inside another of the same size with minimal
quality loss to either image. Deep neural networks are simultaneously trained to create the …

The appearance of generative adversarial networks (GAN) provides a new approach and
framework for computer vision. Compared with traditional machine learning algorithms, GAN …

As a promising technique of resisting steganalysis detection, generative steganography
usually generates a new image driven by secret information as the stego-image. However, it …