most citedOptimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

8 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20261 cited

Curvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

Salar Adel Sabri, Ramadhan J. Mstafa

The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising serious concerns about digital…

eess.IV20258 cited

Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

Nizheen A. Ali, Ramadhan J. Mstafa

With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of vi…

cs.MM20257 cited

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

Ramadhan J. Mstafa

The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements…

cs.CV20254 cited

A Study of Gender Classification Techniques Based on Iris Images: A Deep Survey and Analysis

Basna Mohammed Salih Hasan, Ramadhan J. Mstafa

Gender classification is attractive in a range of applications, including surveillance and monitoring, corporate profiling, and human-computer interaction. Individuals' identities…

cs.CV2025

Exploring the Feasibility of Deep Learning Techniques for Accurate Gender Classification from Eye Images

Basna Mohammed Salih Hasan, Ramadhan J. Mstafa

Gender classification has emerged as a crucial aspect in various fields, including security, human-machine interaction, surveillance, and advertising. Nonetheless, the accuracy of…