Khalid Saeed

A New Hybrid Fusion Approach Based on Classical Methods (PCA, LBP) and Deep Learning (FaceNet) for Performance Improvement of Face Recognition Methods

The proposed FLLF method, which fuses FaceNet embeddings with PCA-whitened LBP descriptors at the feature level and classifies them with a calibrated linear SVM, further improved accuracy to approximately 98.5% and produced the highest prediction confidence values of all tested methods.