PhD Candidates
Opeyemi Bamigbade
Forensics and Security Research Group
Opeyemi Bamigbade is a PhD candidate in the Forensics and Security Research Group. A fuller biography, research profile, and headshot will be added soon.
Research Output
Publications
VAAS: Vision-Attention Anomaly Scoring for image manipulation detection in digital forensics
Forensic Science International: Digital Investigation Vol. 56 pp. 302063
VAAS detects image manipulation using Vision Transformers and segmentation embeddings, providing a continuous anomaly score for digital forensics.
Improving Image Embeddings with Colour Features in Indoor Scene Geolocation
IEEE Access Vol. 13
This paper proposes a model architecture that integrates image N-dominant colours and colour histogram vectors with image embedding from deep metric learning and classification perspectives to improve image geolocation in indoor scenes.
Perceptual Colour-based Geolocation of Human Trafficking Images for Digital Forensic Investigation
2024 Cyber Research Conference - Ireland (Cyber-RCI)
This study investigates the effectiveness of colour-based descriptors in Content-Based Image Retrieval (CBIR) for human trafficking image analysis. The research evaluates the impact of various parameters on image matching accuracy, achieving a Top-50 accuracy of over 95% on the Hotels-50K dataset. The approach demonstrates potential in advancing image analysis tools for human trafficking investigations and other contexts.