Ph.D. Thesis - Scalable Human Identification with Deep Learning
Multi-view Multi-Human Association with Deep Assignment Network, IEEE TIP 2022.
A multi‑country synthetic identity generator that produces full, internally consistent life profiles (personal data, family, employment history, historical context, etc.) designed for OPSEC, security research, and testing scenarios, never for impersonation of real individuals or any unlawful use.
Advanced Gait Recognition system using Multimodal Fusion of RGB-D Optical Flow and IMU Kinematics. Features SVM classification, PCA reduction, and XAI forensic tools.
A robust Multimodal Gait Recognition System early-fusing synchronized RGB-D-IR Optical Flow and Wearable IMU data. Evaluated on the F-BioGate dataset under strict cross-session Closed Set (Identification) and Open Set (Watchlist) protocols using optimized Machine Learning architectures.
Hybrid Gait-Based Human Identification Using Modified U-Net and Score-Level Fusion
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