Explore MATLAB source code curated for "人脸识别" with clean implementations, documentation, and examples.
MATLAB source code for face recognition using Regularized Linear Discriminant Analysis (RLDA) with related reference papers. This implementation includes feature extraction, regularization parameter optimization, and classification components with detailed code comments.
Source code for PCA feature extraction, particularly useful for face recognition applications with algorithm implementation details
A basic MATLAB face recognition implementation featuring a personal image database and fundamental image processing techniques
A complete MATLAB-based face recognition program utilizing Principal Component Analysis (PCA) algorithm, featuring practical implementation with detailed code structure and mathematical foundation
MATLAB implementation of face recognition using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms with complete source code and detailed technical explanations.
Latest AP clustering algorithm implementation and demo program based on the scientific paper "Affinity Propagation" published in Science, featuring efficient similarity matrix computation and cluster center selection.
Face recognition implementation example including project objectives, proposed solutions, implementation programs, and required toolboxes with code-level explanations
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.
PCA Face Detection and Recognition - Content: Face Eigenvalue Extraction, Face Model Reconstruction, and Face Recognition with Implementation Details
Comprehensive routines for sparse representation face recognition algorithms accompanied by l1magic PDF documentation and code implementation details