Dr Farah Ahmed

Assistant Professor

School: Computer Science

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Key Publications

Please visit the Pure Research Information Portal for further information
Source Camera Model Identification in Smartphone Videos Using Fused Features from Separated Noise Residuals, Farzadpour, Z., Ahmed, F., Khelifi, F. 4 Mar 2026, Seventeenth International Conference on Graphics and Image Processing, ICGIP 2025, Bellingham, US, SPIE
Digital twins for smart asset management in the energy industry: State-of-the-art, Amin, U., Kim, D., Ahmed, F., Ahmad, G., Hossain, M. 15 Sep 2025, In: Expert Systems with Applications
A machine learning-based approach for picture acquisition timeslot prediction using defective pixels, Ahmed, F., Khelifi, F., Lawgaly, A., Bouridane, A. 1 Dec 2021, In: Forensic Science International: Digital Investigation
Temporal image forensic analysis for picture dating with deep learning, Ahmed, F., Khelifi, F., Lawgaly, A., Bouridane, A. 17 Aug 2020, Proceedings - 2020 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020, IEEE
The ‘Northumbria Temporal Image Forensics’ Database: Description and Analysis, Ahmed, F., Khelifi, F., Lawgaly, A., Bouridane, A. 29 Jun 2020, 7th International Conference on Control, Decision and Information Technologies (CoDIT), Piscataway, NJ, IEEE
Comparative Analysis of a Deep Convolutional Neural Network for Source Camera Identification, Ahmed, F., Khelifi, F., Lawgaly, A., Bouridane, A. 16 Jan 2019, Proceedings of 12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019, Piscataway, NJ, IEEE
E²MR: Energy-efficient multipath routing protocol for underwater wireless sensor networks, Khalid, M., Ahmed, F., Arshad, M., Khalid, W., Ahmad, N., Cao, Y. 1 Sep 2019, In: IET Networks

Professional Activity

Please visit the Pure Research Information Portal for further information
Publication Peer-review: Forensic Science International: Digital Investigation (Journal) 2021

PGR Supervision

Zahra Farzadpour Digital video forensics analysis with deep neural networks for video forgery detection and smartphone identification. Start Date: 01/10/2023