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 …

Steganalysis, a field devoted to detecting concealed information in various forms of digital
media, including text, images, audio, and video files, has evolved significantly over time …

Hiding secret data in digital multimedia has been essential to protect the data. Nevertheless,
attackers with a steganalysis technique may break them. Existing steganalysis methods …

Locating hidden data in digital images, otherwise called steganalysis, is a process of
identifying the existence of secret messages within digital images. Steganalysis is used to …

Progress in Deep Learning (DL) has introduced alternative methods for tackling complex
challenges, such as the steganalysis of spatial domain images, where Convolutional Neural …

The principal investigations in image steganalysis in the spatial domain have concentrated
on convolutional neural network (CNN) designs. However, existing CNNs increase the local …

Image steganalysis based on convolutional neural networks (CNN) has attracted great
attention. However, existing networks lack attention to regional features with complex …

This work presents a framework for coffee maturity classification from multispectral image
data based on Convolutional Neural Networks (CNNs). The system leverages the use of …

Technology advancements made machine learning algorithms crucial to solving complex
problems. Deep learning, a machine learning paradigm to design convolutional neural …

The development of deep convolutional neural networks has been largely responsible for
the significant strides forward made in steganography over the past decade. In the field of …