most citedCurvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

1 citations · 1 across the 1 of their papers we have counts for

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7 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.IV2025

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.MM2025

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.CV2025

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…

eess.SP2025

A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis

Mohammed Guhdar, Ramadhan J. Mstafa, Abdulhakeem O. Mohammed

The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient assessment, especially in synchrono…