A hybrid method based on the completely positive-tensors and PCA for face recognition

A tensor is a valuable tools for compressing data in different formats and is widely used in fields such as image processing, artificial intelligence, and data science. Conversely, principal component analysis (PCA), a statistical method for dimensionality reduction, is extensively used in image processing. This research investigates the joint utilization of tensor and PCA methods in face recognition. Our findings suggest that these methods provide specific advantages, such as high efficiency, improved accuracy, and manageable computational expenses.