In today's world of engineering evolution, the need for optimized design has led to
development of a plethora of optimization algorithms. Right from hardware engineering …

Feature selection can remove redundant and useless features, which is an essential way to
improve steganalysis efficiency. However, with the diversity of steganalysis features, feature …

A large number of engineering, science, and computational problems have yet to be solved
in a computationally efficient way. One of the emerging challenges is how evolving …

Steganalysis feature selection shows excellent effectiveness on elevating the detection
efficiency and decreasing time-space cost. However, the single evaluation criterion for …

This paper develops five new discrete Symbiotic Organisms Search (SOS) algorithms for
simultaneous optimization of feature subset and neighborhood size of k-nearest neighbor …

Steganalysis is the art and skill of discriminating stego images from cover images. Image
steganalysis algorithms can be divided into two broad categories, specific and universal. In …

For recognizing speakers in video streams, significant research studies have been made to
obtain a rich machine learning model by extracting high-level speaker's features such as …

Image steganalysis involves the discovery of secret information embedded in an image. The
common method is blind image steganalysis, which is a two‐class classification problem …

Abstract In Mohammadi et al.(Evolutionary computation, optimization and learning
algorithms for data science. arXiv preprint, arXiv: 1908.08006, 2019), we have explored the …

Learning to learn plays a pivotal role in meta-learning (MTL) to obtain an optimal learning
model. In this paper, we investigate image recognition for unseen categories of a given …