YALE Face Database: A Comprehensive Toolkit for Face Recognition Research

YALE Face Database contains 15 subjects with 11 facial images per person, providing robust data for developing and testing face recognition algorithms through various lighting conditions and expressions.

Face Recognition Testing and Usage on ORL, Yale, and AR Face Databases

This code is designed for face recognition applications and can be tested and utilized on standard face databases including ORL, Yale, and AR. The implementation incorporates feature extraction and matching algorithms to compare input facial images against database templates.

Loaded ORL and YALE Face Database Data for Machine Learning

Pre-processed ORL and YALE face database datasets ready for machine learning applications. When loaded using LODA, the 'train' variable contains training samples while 'test' represents testing samples, following standard dataset partitioning for model training and evaluation.