Dr Farah Ahmed

• 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

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

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

Computer Studies PhD October 13 2021